[Federal Register: April 7, 2005 (Volume 70, Number 66)]
[Notices]
[Page 17765-17817]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
[DOCID:fr07ap05-133]
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Part II
Environmental Protection Agency
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Notice of Availability; Documents Entitled Guidelines for Carcinogen
Risk Assessment and Supplemental Guidance for Assessing Susceptibility
From Early-Life Exposure to Carcinogens; Notices
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ENVIRONMENTAL PROTECTION AGENCY
[FRL-7895-2]
Notice of Availability of the Document Entitled Guidelines for
Carcinogen Risk Assessment
AGENCY: U.S. Environmental Protection Agency (EPA).
ACTION: Notice of availability of final document.
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SUMMARY: This Notice announces the availability of the final document,
Guidelines for Carcinogen Risk Assessment (EPA/630/P-03/001F),
hereafter referred to as the Guidelines. These Guidelines were
developed as part of an Agency-wide guidelines development program by a
Technical Panel of the U.S. EPA's Risk Assessment Forum, which was
composed of scientists from throughout the Agency. Selected drafts were
peer reviewed internally by the U.S. EPA's Science Advisory Board, and
by experts from universities, environmental groups, industry and other
governmental agencies. The Guidelines were also subjected to several
public comment periods. Issuance of these final Guidelines fulfills
EPA's obligations under section 112(o) (7) of the Clean Air Act.
DATES: The Guidelines are available for use by EPA risk assessors as
March 29, 2005.
ADDRESSES: This Notice contains the full Guidelines document. The
Guidelines also are available electronically through the EPA Web site
at http://www.epa.gov/cancerguidelines. A limited number of paper and
CDROM copies will be available from the EPA's National Service Center
for Environmental Publications (NSCEP), P.O. Box 42419, Cincinnati, OH
45242; telephone: (800) 490-9198 or (513) 489-8190; facsimile: (513)
489-8695. Please provide your name, mailing address and the title and
number of the requested EPA publication (EPA/630/P-03-001F).
Additionally, copies of the Guidelines will be available for inspection
at EPA headquarters and regional libraries, through the U.S. Government
Depository Library program.
FOR FURTHER INFORMATION CONTACT: Dr. William P. Wood, Risk Assessment
Forum, National Center for Environmental Assessment (8601D), U.S.
Environmental Protection Agency, Washington DC 20460, telephone: (202)
564-3361; facsimile: (202) 565-0062; or e-mail:
risk.forum@epamail.epa.gov.
SUPPLEMENTARY INFORMATION: In the 1983 Risk Assessment in the Federal
Government: Managing the Process, the National Academy of Sciences
recommended that Federal regulatory agencies establish ``inference
guidelines'' to promote consistency and technical quality in risk
assessment, and to ensure that the risk assessment process is
maintained as a scientific effort separate from risk management. A task
force within EPA accepted that recommendation and requested that EPA
scientists begin to develop such guidelines. In 1984, EPA scientists
began work on risk assessment guidelines for carcinogenicity,
mutagenicity, suspect developmental toxicants, chemical mixtures and
exposure assessment. Following extensive scientific and public review,
these five guidelines were issued on September 24, 1986 (51 FR 33992-
34054). Since 1986, additional risk assessment guidelines have been
developed, revised and supplemented.
EPA continues to revisit the guidelines as experience and
scientific consensus evolve. In 1996, the Agency published proposed
revisions to EPA's 1986 cancer guidelines for public comment. Since the
1996 proposal, the document has undergone extensive public comment and
scientific peer review, including three reviews by EPA's Science
Advisory Board (SAB) in February 1997, January 1999 and July 1999. The
July 1999 review panel was supplemented by the EPA Children's Health
Protection Advisory Committee. Public comments were received concurrent
to each of these reviews. In 2001 (66 FR 59593, November 29, 2001) an
additional public comment period was held requesting new information
gained through the use of the July 1999 draft final revised guidelines
on issues including, but not limited to, the nature and use of default
assumptions; definition and application of hazard descriptors;
identification of carcinogenic mode(s) of action and, in particular,
consideration of relevancy for children (e.g., the potential for
differential life stage susceptibility); and guidance on the use of the
margin of exposure analysis. The notice also announced that the July
1999 draft final revised guidelines would serve as EPA's interim
guidance to EPA risk assessors preparing cancer risk assessment, until
the issuance of final guidelines. In May 2003 EPA made available for
public comment a revised draft of the guidelines, and in February 2005
the guidelines underwent interagency review. The final Guidelines
issued today are based, in part, upon the recommendations derived from
public comments, workshops and recommendations of the SAB.
CAA section 112(o)(7) provides ``[t]he Administrator shall
consider, but need not adopt, the recommendations contained in the
report of the National Academy of Sciences prepared pursuant to this
subsection and the views of the Science Advisory Board, with respect to
such report. Prior to the promulgation of any standard under [CAA
section 112(f)], and after notice and opportunity for comment, the
Administrator shall publish revised Guidelines for Carcinogenic Risk
Assessment or a detailed explanation of the reasons that any
recommendations contained in the report of the National Academy of
Sciences will not be implemented.''
In response to CAA section 112(o)(7), the 1994 National Research
Council (NRC) report, and continuing developments in the science of
cancer risk assessment, EPA began the process of revising its
Guidelines for Carcinogen Risk Assessment. Revisions to the Guidelines
were intended to make greater use of the increasing scientific
understanding of the mechanisms that underlie the carcinogenic process.
Several drafts of revisions to the Guidelines have been subject to
extensive public comment and scientific peer review, including three
reviews by EPA's SAB, as discussed above. EPA considered the 1994
recommendations of the NRC on the Guidelines. EPA's approach to those
NRC recommendations is reflected in the Guidelines. Draft EPA responses
to the NRC recommendations were presented in the preamble to the 1996
draft of these revised Guidelines (61 FR 18003, April 23, 1996). By
issuing the final Guidelines which address the recommendations of the
NRC, EPA has fulfilled its responsibilities under CAA section
112(o)(7).
Features of the Guidelines
The Guidelines are intended to make greater use of the increasing
scientific understanding of the mechanisms that underlie the
carcinogenic process. The final guidelines include discussions of all
of the four steps of the risk assessment process and provide guidance
to risk assessors on these steps. In applying these principles to the
development of these Guidelines, the following key issues were
highlighted: use of default options, the consideration of mode of
action, understanding of biological changes, fuller characterization of
carcinogenic potential, and consideration of differences in
susceptibility.
Use of default options--Default options are approaches that EPA can
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apply in risk assessments when scientific information about the effects
of an agent on human health is unavailable, limited, or of insufficient
quality. Under the final Guidelines, EPA's approach begins with a
critical analysis of available information, and then invokes defaults
if needed to address uncertainty or the absence of critical
information.
Consideration of mode of action--Cancer refers to a group of
diseases involving abnormal, malignant tissue growth. Research has
revealed that the development of cancer involves a complex series of
steps and that carcinogens may operate in a number of different ways.
The final Guidelines emphasize the value of understanding the
biological changes and how these changes might lead to the development
of cancer. They also discuss ways to evaluate and use such information,
including information about an agent's postulated mode of action, or
the series of steps and processes that lead to cancer formation. Mode-
of-action data, when available and of sufficient quality, may be used
to draw conclusions about the potency of a chemical, its potential
effects at low doses, whether findings in animals are relevant to
humans, and which populations or lifestages may be particularly
susceptible.
Fuller characterization of carcinogenic potential--In the final
Guidelines, an agent's human carcinogenic potential is described in a
weight-of-evidence narrative. The narrative summarizes the full range
of available evidence and describes any conditions associated with
conclusions about an agent's hazard potential. For example, the
narrative may explain that a chemical appears to be carcinogenic by
some routes of exposure but not by others (e.g., by inhalation but not
ingestion). Similarly, a hazard may be attributed to exposures during
sensitive life-stages of development but not at other times. The
narrative also summarizes uncertainties and key default options that
have been invoked. To provide additional clarity and consistency in
weight-of-evidence narratives, the Guidelines present a set of weight-
of-evidence descriptors that accompany the narratives. The Guidelines
emphasize that risk managers should consider the full range of
information in the narratives and not focus exclusively on the
descriptors. As in the case of the narratives, descriptors may apply
only to certain routes of exposure, dose ranges and durations of
exposure.
Consideration of differences in susceptibility--The Guidelines
explicitly recognize that variation may exist among people in their
susceptibility to carcinogens. Some subpopulations may experience
increased susceptibility to carcinogens throughout their life, such as
people who have inherited predisposition to certain cancer types or
reduced capacity to repair genetic damage. Also, during certain
lifestages the entire population may experience heightened
susceptibility to carcinogens. In particular, EPA notes that childhood
may be a lifestage of greater susceptibility for a number of reasons:
rapid growth and development that occurs prenatally and after birth,
differences related to an immature metabolic system, and differences in
diet and behavior patterns that may increase exposure.
The final Guidelines explicitly call for consideration of possible
sensitive subpopulations and/or lifestages (such as childhood).
Therefore, concurrent with release of the final Guidelines, EPA
published a separate guidance, entitled Supplemental Guidance for
Assessing Susceptibility from Early-Life Exposure to Carcinogens (EPA/
630/R-03/003F), hereafter referred to as the Supplemental Guidance,
describing possible approaches that could be used to assess risks
resulting from early life exposure to potential carcinogens. The
Supplemental Guidance is separate from the Guidelines so that it may be
more easily updated in a timely manner given the expected rapid
evolution of scientific understanding about the effects of early-life
exposures. Availability of the Supplemental Guidance is announced in a
separate notice, also published in today's Federal Register.
Risk Assessment Guidelines at EPA
These Guidelines set forth principles and procedures to guide EPA
scientists in the conduct of cancer risk assessments and to inform
Agency decision makers and the public about these procedures. Policies
in this document are intended as internal guidance for EPA. So risk
assessors and risk managers at EPA are the primary audience. These
Guidelines also provide basic information to the public about EPA's
risk assessment methods. In particular, the Guidelines emphasize that
risk assessments should be conducted on a case-by-case basis, giving
full consideration to all relevant scientific information. This
approach means that Agency experts study scientific information on each
agent under review and use the most scientifically appropriate
interpretation to assess risk. The Guidelines also stress that this
information be fully presented in Agency risk assessment documents, and
that Agency scientists identify the strengths and weaknesses of each
assessment by describing uncertainties, assumptions and limitations, as
well as the scientific basis and rationale for each assessment. The
Guidelines are formulated in part to bridge gaps in risk assessment
methodology and data. By identifying these gaps and the importance of
the missing information to the risk assessment process, EPA wishes to
encourage research and analysis that will lead to new risk assessment
methods and data.
The Guidelines are guidance only. They do not establish any
substantive ``rules'' under the Administrative Procedure Act or any
other law and have no binding effect on EPA or any regulated entity,
but instead will represent a non-binding statement of policy. EPA
believes that the Guidelines represent a sound and up-to-date approach
to cancer risk assessment and enhance the application of the best
available science in EPA's risk assessments. However, EPA cancer risk
assessments may be conducted differently than envisioned in the
Guidelines for many reasons, including (but not limited to) new
information, new scientific understanding or new science policy
judgment. The science of risk assessment continues to develop rapidly,
and specific components of the Guidelines may become outdated or may
otherwise require modification in individual settings. Use of the
Guidelines in future risk assessments will be based on decisions by EPA
that approaches from the Guidelines are suitable and appropriate in the
context of those particular risk assessments. These judgments will be
tested through peer review, and risk assessments will be modified to
use different approaches if appropriate.
Even though the Guidelines are not binding rules, EPA is issuing
them in a manner consistent with the procedures in the Administrative
Procedure Act that are generally applicable to rulemaking, including
providing opportunity for public comment. EPA considered and responded
to all significant public comments as it prepared the Guidelines and
will send a copy of the final Guidelines to Congress. EPA certifies
that the Guidelines will not have a significant impact on a substantial
number of small entities, because the Guidelines are for the benefit of
EPA and impose no requirements or costs on small entities.
Implementation
Beginning today, Guidelines and Supplemental Guidance serve as
EPA's
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recommendation to Agency risk assessors preparing cancer risk
assessments. As EPA prepares cancer assessments under the Integrated
Risk Information System (IRIS) program, as well as in other EPA
programs, the Agency intends to begin to use the Guidelines and
Supplemental Guidance. EPA also intends to consider the Guidelines and
Supplemental Guidance along with other selection factors when EPA
selects agents for reassessment in annual IRIS agendas (see for
example, 70 FR 10616, March 4, 2005).
Dated: March 29, 2005.
Stephen L. Johnson,
Acting Administrator.
Contents
1. Introduction
1.1. Purpose and Scope of the Guidelines
1.2. Organization and Application of the Guidelines
1.2.1. Organization
1.2.2. Application
1.3. Key Features of the Cancer Guidelines
1.3.1. Critical Analysis of Available Information as the
Starting Point for Evaluation
1.3.2. Mode of Action
1.3.3. Weight of Evidence Narrative
1.3.4. Dose-response Assessment
1.3.5. Susceptible Populations and Lifestages
1.3.6. Evaluating Risks from Childhood Exposures
1.3.7. Emphasis on Characterization
2. Hazard Assessment
2.1. Overview of Hazard Assessment and Characterization
2.1.1. Analyses of Data
2.1.2. Presentation of Results
2.2. Analysis of Tumor Data
2.2.1. Human Data
2.2.1.1. Assessment of Evidence of Carcinogenicity From Human
Data
2.2.1.2. Types of Studies
2.2.1.3. Exposure Issues
2.2.1.4. Biological Markers
2.2.1.5. Confounding Actors
2.2.1.6. Statistical Considerations
2.2.1.6.1. Likelihood of Observing an Effect
2.2.1.6.2. Sampling and Other Bias Issues
2.2.1.6.3. Combining Statistical Evidence Across Studies
2.2.1.7. Evidence for Causality
2.2.2. Animal Data
2.2.2.1. Long-term Carcinogenicity Studies
2.2.2.1.1. Dosing Issues
2.2.2.1.2. Statistical Considerations
2.2.2.1.3. Concurrent and Historical Controls
2.2.2.1.4. Assessment of Evidence of Carcinogenicity From Long-
term Animal Studies
2.2.2.1.5. Site Concordance
2.2.2.2. Perinatal Carcinogenicity Studies
2.2.2.3. Other Studies
2.2.3. Structural Analogue Data
2.3. Analysis of Other Key Data
2.3.1. Physicochemical Properties
2.3.2. Structure-Activity Relationships
2.3.3. Comparative Metabolism and Toxicokinetics
2.3.4. Toxicological and Clinical Findings
2.3.5. Events Relevant to Mode of Carcinogenic Action
2.3.5.1. Direct DNA-Reactive Effects
2.3.5.2. Indirect DNA Effects or Other Effects on Genes/Gene
Expression
2.3.5.3. Precursor Events and Biomarker Information
2.3.5.4. Judging Data
2.4. Mode of Action--General Considerations and Framework for
Analysis
2.4.1. General Considerations
2.4.2. Evaluating a Hypothesized Mode of Action
2.4.2.1. Peer Review
2.4.2.2. Use of the Framework
2.4.3. Framework for Evaluating Each Hypothesized Carcinogenic
Mode of Action
2.4.3.1. Description of the Hypothesized Mode of Action
2.4.3.2. Discussion of the Experimental Support for the
Hypothesized Mode of Action
2.4.3.3. Consideration of the Possibility of Other Modes of
Action
2.4.3.4. Conclusions About the Hypothesized Mode of Action
2.4.4. Evolution with Experience
2.5. Weight of Evidence Narrative
2.6. Hazard Characterization
3. Dose-Response Assessment
3.1. Analysis of Dose
3.1.1. Standardizing Different Experimental Dosing Regimens
3.1.2. Toxicokinetic Data and Modeling
3.1.3. Cross-species Scaling Procedures
3.1.3.1. Oral Exposures
3.1.3.2. Inhalation Exposures
3.1.4. Route Extrapolation
3.2. Analysis in the Range of Observation
3.2.1. Epidemiologic Studies
3.2.2. Toxicodynamic (``Biologically Based'') Modeling
3.2.3. Empirical Modeling (``Curve Fitting'')
3.2.4. Point of Departure (POD)
3.2.5. Characterizing the POD: The POD Narrative
3.2.6. Relative Potency Factors
3.3. Extrapolation to Lower Doses
3.3.1. Choosing an Extrapolation Approach
3.3.2. Extrapolation Using a Toxicodynamic Model
3.3.3. Extrapolation Using a Low-dose Linear Model
3.3.4. Nonlinear Extrapolation to Lower Doses
3.3.5. Comparing and Combining Multiple Extrapolations
3.4. Extrapolation to Different Human Exposure Scenarios
3.5. Extrapolation to Susceptible Populations and Lifestages
3.6. Uncertainty
3.7. Dose-Response Characterization
4. Exposure Assessment
4.1. Defining the Assessment Questions
4.2. Selecting or Developing the Conceptual and Mathematical
Models
4.3. Collecting Data or Selecting and Evaluating Available Data
4.3.1. Adjusting Unit Risks for Highly Exposed Populations and
Lifestages
4.4. Exposure Characterization
5. Risk Characterization
5.1. Purpose
5.2. Application
5.3. Presentation of the Risk Characterization Summary
5.4. Content of the Risk Characterization Summary
Appendix: Major Default Options
Appendix B: EPA's Guidance for Data Quality Assessment
References
List of Figures
Figure 1-1. Flow chart for early-life risk assessment using mode of
action framework
Figure 3-1. Compatibility of Alternative Points of Departure with
Observed and Modeled Tumor Incidences
Figure 3-2. Crossing between 10% and 1% Dose-Response Curves for
Bladder Carcinomas and Liver Carcinomas Induced by 2-AAF
1. Introduction
1.1. Purpose and Scope of the Guidelines
These guidelines revise and replace the U.S. Environmental
Protection Agency's (EPA's, or the Agency's) Guidelines for Carcinogen
Risk Assessment, published in 51 FR 33992, September 24, 1986 (U.S.
EPA, 1986a) and the 1999 interim final guidelines (U.S. EPA, 1999a; see
U.S. EPA 2001b). They provide EPA staff with guidance for developing
and using risk assessments. They also provide basic information to the
public about the Agency's risk assessment methods.
These cancer guidelines are used with other risk assessment
guidelines, such as the Guidelines for Mutagenicity Risk Assessment
(U.S. EPA, 1986b) and the Guidelines for Exposure Assessment (U.S. EPA,
1992a). Consideration of other Agency guidance documents is also
important in assessing cancer risks where procedures for evaluating
specific target organ effects have been developed (e.g., assessment of
thyroid follicular cell tumors, U.S. EPA, 1998a). All of EPA's
guidelines should be consulted when conducting a risk assessment in
order to ensure that information from studies on carcinogenesis and
other health effects are considered together in the overall
characterization of risk. This is particularly true in the case in
which a precursor effect for a tumor is also a precursor or endpoint of
other health effects or when there is a concern for a particular
susceptible life-stage for which the Agency has developed guidance, for
example, Guidelines for Developmental Toxicity Risk Assessment (U.S.
EPA, 1991a). The developmental guidelines discuss hazards to children
that may result from exposures during preconception and prenatal or
postnatal development to
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sexual maturity. Similar guidelines exist for reproductive toxicant
risk assessments (U.S. EPA, 1996a) and for neurotoxicity risk
assessment (U.S. EPA, 1998b). The overall characterization of risk is
conducted within the context of broader policies and guidance such as
Executive Order 13045, ``Protection of Children From Environmental
Health Risks and Safety Risks'' (Executive Order 13045, 1997) which is
the primary directive to Federal agencies and departments to identify
and assess environmental health risks and safety risks that may
disproportionately affect children.
The cancer guidelines encourage both consistency in the procedures
that support scientific components of Agency decision making and
flexibility to allow incorporation of innovations and contemporaneous
scientific concepts. In balancing these goals, the Agency relies on
established scientific peer review processes (U.S. EPA, 2000a; OMB
2004). The cancer guidelines incorporate basic principles and science
policies based on evaluation of the currently available information.
The Agency intends to revise these cancer guidelines when substantial
changes are necessary. As more information about carcinogenesis
develops, the need may arise to make appropriate changes in risk
assessment guidance. In the interim, the Agency intends to issue
special reports, after appropriate peer review, to supplement and
update guidance on single topics (e.g., U.S. EPA, 1991b). One such
guidance document, Supplemental Guidance for Assessing Susceptibility
from Early-Life Exposure to Carcinogens (``Supplemental Guidance''),
was developed in conjunction with these cancer guidelines (U.S. EPA.,
2005). Because both the methodology and the data in the Supplemental
Guidance (see Section 1.3.6) are expected to evolve more rapidly than
the issues addressed in these cancer guidelines, the two were developed
as separate documents. The Supplemental Guidance, however, as well as
any other relevant (including subsequent) guidance documents, should be
considered along with these cancer guidelines as risk assessments for
carcinogens are generated. The use of supplemental guidance, such as
the Supplemental Guidance for Assessing Cancer Susceptibility from
Early-life Exposure to Carcinogens, has the advantage of allowing the
Supplemental Guidance to be modified as more data become available.
Thus, the consideration of new, peer-reviewed scientific understanding
and data in an assessment can always be consistent with the purposes of
these cancer guidelines.
These cancer guidelines are intended as guidance only. They do not
establish any substantive ``rules'' under the Administrative Procedure
Act or any other law and have no binding effect on EPA or any regulated
entity, but instead represent a non-binding statement of policy. EPA
believes that the cancer guidelines represent a sound and up-to-date
approach to cancer risk assessment, and the cancer guidelines enhance
the application of the best available science in EPA's risk
assessments. However, EPA cancer risk assessments may be conducted
differently than envisioned in the cancer guidelines for many reasons,
including (but not limited to) new information, new scientific
understanding, or new science policy judgment. The science of risk
assessment continues to develop rapidly, and specific components of the
cancer guidelines may become outdated or may otherwise require
modification in individual settings. Use of the cancer guidelines in
future risk assessments will be based on decisions by EPA that the
approaches are suitable and appropriate in the context of those
particular risk assessments. These judgments will be tested through
peer review, and risk assessments will be modified to use different
approaches if appropriate.
1.2. Organization and Application of the Cancer Guidelines
1.2.1. Organization
Publications by the Office of Science and Technology (OSTP, 1985)
and the National Research Council (NRC) (NRC, 1983, 1994) provide
information and general principles about risk assessment. Risk
assessment uses available scientific information on the properties of
an agent \1\ and its effects in biological systems to provide an
evaluation of the potential for harm as a consequence of environmental
exposure. The 1983 and 1994 NRC documents organize risk assessment
information into four areas: Hazard identification, dose-response
assessment, exposure assessment, and risk characterization. This
structure appears in these cancer guidelines, with additional emphasis
placed on characterization of evidence and conclusions in each area of
the assessment. In particular, the cancer guidelines adopt the approach
of the NRC's 1994 report in adding a dimension of characterization to
the hazard identification step: an evaluation of the conditions under
which its expression is anticipated. Risk assessment questions
addressed in these cancer guidelines are as follows.
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\1\ The term ``agent'' refers generally to any chemical
substance, mixture, or physical or biological entity being assessed,
unless otherwise noted (See Section 1.2.2 for a note on radiation.).
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For hazard--Can the identified agent present a
carcinogenic hazard to humans and, if so, under what circumstances?
For dose response--At what levels of exposure might
effects occur?
For exposure--What are the conditions of human exposure?
For risk--What is the character of the risk? How well do
data support conclusions about the nature and extent of the risk from
various exposures?
The risk characterization process first summarizes findings on
hazard, dose response, and exposure characterizations and then develops
an integrative analysis of the whole risk case. It ends in the writing
of a technical risk characterization. Other documents, such as
summaries for the risk managers and the public, reflecting the key
points of the risk characterization are usually written. A summary for
managers is a presentation for those who may or may not be familiar
with the scientific details of cancer assessment. It also provides
information for other interested readers. The initial steps in the risk
characterization process are to make building blocks in the form of
characterizations of the assessments of hazard, dose response, and
exposure. The individual assessments and characterizations are then
integrated to arrive at risk estimates for exposure scenarios of
interest. As part of the characterization process, explicit evaluations
are made of the hazard and risk potential for susceptible lifestages,
including children (U.S. EPA, 1995, 2000b).
The 1994 NRC document also explicitly called attention to the role
of the risk assessment process in identifying scientific uncertainties
that, if addressed, could serve to reduce their uncertainty in future
iterations of the risk assessment. NRC recommended that when the Agency
``reports estimates of risk to decisions-makers and the public, it
should present not only point estimates of risk, but also the sources
and magnitudes of uncertainty associated with these estimates'' (p.
15). Thus, the identified uncertainties serve as a feedback loop to the
research community and decisionmakers, specifying areas and types of
information that would be particularly useful.
There are several reasons for individually characterizing the
hazard, dose response, and exposure
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assessments. One is that they are often done by different people than
those who do the integrative analyses. The second is that there is very
often a lapse of time between the conduct of hazard and dose-response
analyses and the conduct of exposure assessment and integrative
analysis. Thus, it is important to capture characterizations of
assessments as the assessments are done to avoid the need to go back
and reconstruct them. Finally, frequently a single hazard assessment is
used by several programs for several different exposure scenarios.
There may be one or several documents involved. ``Integrative
analysis'' is a generic term; and many documents that have other titles
may contain integrative analyses. In the following sections, the
elements of these characterizations are discussed.
1.2.2. Application
The cancer guidelines apply within the framework of policies
provided by applicable EPA statutes and do not alter such policies.
The cancer guidelines cover the assessment of available
data. They do not imply that one kind of data or another is
prerequisite for regulatory action concerning any agent. It is
important that, when evaluating and considering the use of any data,
EPA analysts incorporate the basic standards of quality, as defined by
the EPA Information Quality Guidelines (U.S. EPA, 2002a see Appendix B)
and other Agency guidance on data quality such as the EPA Quality
Manual for Environmental Programs (U.S. EPA, 2000e), as well as OMB
Guidelines for Ensuring and Maximizing the Quality, Utility, and
Integrity of Information Disseminated by Federal Agencies (OMB, 2002).
It is very important that all analyses consider the basic standards of
quality, including objectivity, utility, and integrity. A summary of
the factors and considerations generally used by the Agency when
evaluating and considering the use of scientific and technical
information is contained in EPA's A Summary of General Assessment
Factors for Evaluating the Quality of Scientific and Technical
Information (U.S. EPA, 2003).
Risk management applies directives in statutes, which may
require consideration of potential risk or solely hazard or exposure
potential, along with social, economic, technical, and other factors in
decision making. Risk assessments may be used to support decisions, but
in order to maintain their integrity as decision-making tools, they are
not influenced by consideration of the social or economic consequences
of regulatory action.
The assessment of risk from radiation sources is informed by the
continuing examination of human data by the National Academy of
Sciences/NRC in its series of numbered reports: ``Biological Effects of
Ionizing Radiation.'' Although some of the general principles of these
cancer guidelines may also apply to radiation risk assessments, some of
the details of their risk assessment procedures may not, as they are
most focused on other kinds of agents. Therefore, these cancer
guidelines are not intended to provide the primary source of, or
guidance for, the Agency's evaluation of the carcinogenic risks of
radiation.
Not every EPA assessment has the same scope or depth, a factor
recognized by the National Academy of Sciences (NRC, 1996). For
example, EPA's Information Quality Guidelines (U.S. EPA, 2002a, see
Appendix B) discuss influential information that ``will have or does
have a clear and substantial impact * * * on important public policies
or private sector decisions * * * that should adhere to a rigorous
standard of quality.'' It is often difficult to know a priori how the
results of a risk assessment are likely to be used by the Agency. Some
risk assessments may be used by Agency economists and policy analysts,
and the necessary information for such analyses, as discussed in detail
later in this document, should be included when practicable (U.S. EPA,
2002a). On the other hand, Agency staff often conduct screening-level
assessments for priority setting or separate assessments of hazard or
exposure for ranking purposes or to decide whether to invest resources
in collecting data for a full assessment. Moreover, a given assessment
of hazard and dose response may be used with more than one exposure
assessment that may be conducted separately and at different times as
the need arises in studying environmental problems related to various
exposure media. The cancer guidelines apply to these various situations
in appropriate detail, given the scope and depth of the particular
assessment. For example, a screening assessment may be based almost
entirely on structure-activity relationships (SARs) and default
options, when other data are not readily available. When more data and
resources are readily available, assessments can use a critical
analysis of all of the available data as the starting point of the risk
assessment. Under these conditions, default options would only be used
to address uncertainties or the absence of critical data. Default
options are inferences based on general scientific knowledge of the
phenomena in question and are also matters of policy concerning the
appropriate way to bridge uncertainties that concern potential risk to
human health.
These cancer guidelines do not suggest that all of the kinds of
data covered here will need to be available or used for either
assessment or decision making. The level of detail of an assessment is
a matter of Agency management discretion regarding applicable decision-
making needs. The Agency generally presumes that key cancer information
(e.g., assessments contained in the Agency's Integrated Risk
Information System) is ``influential information'' as defined by the
EPA Information Quality Guidelines and ``highly influential'' as
defined by OMB's Information Quality Bulletin for Peer Review (OMB
2004).
1.3. Key Features of the Cancer Guidelines
1.3.1. Critical Analysis of Available Information as the Starting Point
for Evaluation
As an increasing understanding of carcinogenesis is becoming
available, these cancer guidelines adopt a view of default options that
is consistent with EPA's mission to protect human health while adhering
to the tenets of sound science. Rather than viewing default options as
the starting point from which departures may be justified by new
scientific information, these cancer guidelines view a critical
analysis of all of the available information that is relevant to
assessing the carcinogenic risk as the starting point from which a
default option may be invoked if needed to address uncertainty or the
absence of critical information. Preference is given to using
information that has been peer reviewed, e.g., reported in peer-
reviewed scientific journals. The primary goal of EPA actions is
protection of human health; accordingly, as an Agency policy, risk
assessment procedures, including default options that are used in the
absence of scientific data to the contrary, should be health protective
(U.S. EPA, 1999b).
Use of health protective risk assessment procedures as described in
these cancer guidelines means that estimates, while uncertain, are more
likely to overstate than understate hazard and/or risk. NRC (1994)
reaffirmed the use of default options as ``a reasonable way to cope
with uncertainty about the choice of appropriate models or theory'' (p.
104). NRC saw the need to treat uncertainty in a predictable way that
is
[[Page 17771]]
``scientifically defensible, consistent with the agency's statutory
mission, and responsive to the needs of decision-makers'' (p. 86). The
extent of health protection provided to the public ultimately depends
upon what risk managers decide is the appropriate course of regulatory
action. When risk assessments are performed using only one set of
procedures, it may be difficult for risk managers to determine how much
health protectiveness is built into a particular hazard determination
or risk characterization. When there are alternative procedures having
significant biological support, the Agency encourages assessments to be
performed using these alternative procedures, if feasible, in order to
shed light on the uncertainties in the assessment, recognizing that the
Agency may decide to give greater weight to one set of procedures than
another in a specific assessment or management decision.
Encouraging risk assessors to be receptive to new scientific
information, NRC discussed the need for departures from default options
when a ``sufficient showing'' is made. It called on EPA to articulate
clearly its criteria for a departure so that decisions to depart from
default options would be ``scientifically credible and receive public
acceptance'' (p. 91). It was concerned that ad hoc departures would
undercut the scientific credibility of a risk assessment. NRC
envisioned that principles for choosing and departing from default
options would balance several objectives, including ``protecting the
public health, ensuring scientific validity, minimizing serious errors
in estimating risks, maximizing incentives for research, creating an
orderly and predictable process, and fostering openness and
trustworthiness'' (p. 81).
Appendices N-1 and N-2 of NRC (1994) discussed two competing
standards for choosing default options articulated by members of the
committee. One suggested approach would evaluate a departure in terms
of whether ``it is scientifically plausible'' and whether it ``tends to
protect public health in the face of scientific uncertainty'' (p. 601).
An alternative approach ``emphasizes scientific plausibility with
regard to the use of alternative models'' (p. 631). Reaching no
consensus on a single approach, NRC recognized that developing criteria
for departures is an EPA policy matter.
The basis for invoking a default option depends on the
circumstances. Generally, if a gap in basic understanding exists or if
agent-specific information is missing, a default option may be used. If
agent-specific information is present but critical analysis reveals
inadequacies, a default option may also be used. If critical analysis
of agent-specific information is consistent with one or more
biologically based models as well as with the default option, the
alternative models and the default option are both carried through the
assessment and characterized for the risk manager. In this case, the
default model not only fits the data, but also serves as a benchmark
for comparison with other analyses. This case also highlights the
importance of extensive experimentation to support a conclusion about
mode of action, including addressing the issue of whether alternative
modes of action are also plausible. Section 2.4 provides a framework
for critical analysis of mode of action information to address the
extent to which the available information supports the hypothesized
mode of action, whether alternative modes of action are also plausible,
and whether there is confidence that the same inferences can be
extended to populations and lifestages that are not represented among
the experimental data.
Generally, cancer risk decisions strive to be ``scientifically
defensible, consistent with the agency's statutory mission, and
responsive to the needs of decision-makers'' (NRC, 1994). Scientific
defensibility would be evaluated through use of EPA's Science Advisory
Board, EPA's Office of Pesticide Programs' Scientific Advisory Panel,
or other independent expert peer review panels to determine whether a
consensus among scientific experts exists. Consistency with the
Agency's statutory mission would consider whether the risk assessment
overall supports EPA's mission to protect human health and safeguard
the natural environment. Responsiveness to the needs of decisionmakers
would take into account pragmatic considerations such as the nature of
the decision; the required depth of analysis; the utility, time, and
cost of generating new scientific data; and the time, personnel, and
resources allotted to the risk assessment.
With a multitude of types of data, analyses, and risk assessments,
as well as the diversity of needs of decisionmakers, it is neither
possible nor desirable to specify step-by-step criteria for decisions
to invoke a default option. A discussion of major default options
appears in the Appendix. Screening-level assessments may more readily
use default parameters, even worst-case assumptions, that would not be
appropriate in a full-scale assessment. On the other hand, significant
risk management decisions will often benefit from a more comprehensive
assessment, including alternative risk models having significant
biological support. To the extent practicable, such assessments should
provide central estimates of potential risks in conjunction with lower
and upper bounds (e.g., confidence limits) and a clear statement of the
uncertainty associated with these estimates.
In the absence of sufficient data or understanding to develop of a
robust, biologically based model, an appropriate policy choice is to
have a single preferred curve-fitting model for each type of data set.
Many different curve-fitting models have been developed, and those that
fit the observed data reasonably well may lead to several-fold
differences in estimated risk at the lower end of the observed range.
In addition, goodness-of-fit to the experimental observations is not by
itself an effective means of discriminating among models that
adequately fit the data (OSTP, 1985). To provide some measure of
consistency across different carcinogen assessments, EPA uses a
standard curve-fitting procedure for tumor incidence data. Assessments
that include a different approach should provide an adequate
justification and compare their results with those from the standard
procedure. Application of models to data should be conducted in an open
and transparent manner.
1.3.2. Mode of Action
The use of mode of action \2\ in the assessment of potential
carcinogens is a main focus of these cancer guidelines. This area of
emphasis arose because of the significant scientific advances that have
developed concerning the causes of cancer induction. Elucidation of a
mode of action for a particular cancer response in animals or humans is
a data-rich determination. Significant
[[Page 17772]]
information should be developed to ensure that a scientifically
justifiable mode of action underlies the process leading to cancer at a
given site. In the absence of sufficiently, scientifically justifiable
mode of action information, EPA generally takes public health-
protective, default positions regarding the interpretation of
toxicologic and epidemiologic data: Animal tumor findings are judged to
be relevant to humans, and cancer risks are assumed to conform with low
dose linearity.
---------------------------------------------------------------------------
\2\ The term ``mode of action'' is defined as a sequence of key
events and processes, starting with interaction of an agent with a
cell, proceeding through operational and anatomical changes, and
resulting in cancer formation. A ``key event'' is an empirically
observable precursor step that is itself a necessary element of the
mode of action or is a biologically based marker for such an
element. Mode of action is contrasted with ``mechanism of action,''
which implies a more detailed understanding and description of
events, often at the molecular level, than is meant by mode of
action. The toxicokinetic processes that lead to formation or
distribution of the active agent to the target tissue are considered
in estimating dose but are not part of the mode of action as the
term is used here. There are many examples of possible modes of
carcinogenic action, such as mutagenicity, mitogenesis, inhibition
of cell death, cytotoxicity with reparative cell proliferation, and
immune suppression.
---------------------------------------------------------------------------
Understanding of mode of action can be a key to identifying
processes that may cause chemical exposures to differentially affect a
particular population segment or lifestage. Some modes of action are
anticipated to be mutagenic and are assessed with a linear approach.
This is the mode of action of radiation and several other agents that
are known carcinogens. Other modes of action may be modeled with either
linear or nonlinear \3\ approaches after a rigorous analysis of
available data under the guidance provided in the framework for mode of
action analysis (see Section 2.4.3).
---------------------------------------------------------------------------
\3\ The term ``nonlinear'' is used here in a narrower sense than
its usual meaning in the field of mathematical modeling. In these
cancer guidelines, the term ``nonlinear'' refers to threshold models
(which show no response over a range of low doses that include zero)
and some nonthreshold models (e.g., a quadractic model, which shows
some response at all doses above zero). In these cancer guidelines,
a nonlinear model is one whose slope is zero at (and perhaps above)
a dose of zero. A low-dose-linear model is one whose slope is
greater than zero at a dose of zero. A low-dose-linear model
approximates a straight line only at very low doses; at higher doses
near the observed data, a low-dose-linear model can display
curvature. The term ``low-dose-linear'' is often abbreviated
``linear,'' although a low-dose-linear model is not linear at all
doses. Use of nonlinear approaches does not imply a biological
threshold dose below which the response is zero. Estimating
thresholds can be problematic; for example, a response that is not
statistically significant can be consistent with a small risk that
falls below an experiment's power of detection.
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1.3.3. Weight of Evidence Narrative
The cancer guidelines emphasize the importance of weighing all of
the evidence in reaching conclusions about the human carcinogenic
potential of agents. This is accomplished in a single integrative step
after assessing all of the individual lines of evidence, which is in
contrast to the step-wise approach in the 1986 cancer guidelines.
Evidence considered includes tumor findings, or lack thereof, in humans
and laboratory animals; an agent's chemical and physical properties;
its structure-activity relationships (SARs) as compared with other
carcinogenic agents; and studies addressing potential carcinogenic
processes and mode(s) of action, either in vivo or in vitro. Data from
epidemiologic studies are generally preferred for characterizing human
cancer hazard and risk. However, all of the information discussed above
could provide valuable insights into the possible mode(s) of action and
likelihood of human cancer hazard and risk. The cancer guidelines
recognize the growing sophistication of research methods, particularly
in their ability to reveal the modes of action of carcinogenic agents
at cellular and subcellular levels as well as toxicokinetic processes.
Weighing of the evidence includes addressing not only the
likelihood of human carcinogenic effects of the agent but also the
conditions under which such effects may be expressed, to the extent
that these are revealed in the toxicological and other biologically
important features of the agent.
The weight of evidence narrative to characterize hazard summarizes
the results of the hazard assessment and provides a conclusion with
regard to human carcinogenic potential. The narrative explains the
kinds of evidence available and how they fit together in drawing
conclusions, and it points out significant issues/strengths/limitations
of the data and conclusions. Because the narrative also summarizes the
mode of action information, it sets the stage for the discussion of the
rationale underlying a recommended approach to dose-response
assessment.
In order to provide some measure of clarity and consistency in an
otherwise free-form, narrative characterization, standard descriptors
are used as part of the hazard narrative to express the conclusion
regarding the weight of evidence for carcinogenic hazard potential.
There are five recommended standard hazard descriptors: ``Carcinogenic
to Humans,'' ``Likely to Be Carcinogenic to Humans,'' ``Suggestive
Evidence of Carcinogenic Potential,'' ``Inadequate Information to
Assess Carcinogenic Potential,'' and ``Not Likely to Be Carcinogenic to
Humans.'' Each standard descriptor may be applicable to a wide variety
of data sets and weights of evidence and is presented only in the
context of a weight of evidence narrative. Furthermore, as described in
Section 2.5 of these cancer guidelines, more than one conclusion may be
reached for an agent.
1.3.4. Dose-Response Assessment
Dose-response assessment evaluates potential risks to humans at
particular exposure levels. The approach to dose-response assessment
for a particular agent is based on the conclusion reached as to its
potential mode(s) of action for each tumor type. Because an agent may
induce multiple tumor types, the dose-response assessment includes an
analysis of all tumor types, followed by an overall synthesis that
includes a characterization of the risk estimates across tumor types,
the strength of the mode of action information of each tumor type, and
the anticipated relevance of each tumor type to humans, including
susceptible populations and lifestages (e.g., childhood).
Dose-response assessment for each tumor type is performed in two
steps: assessment of observed data to derive a point of departure
(POD),\4\ followed by extrapolation to lower exposures to the extent
that is necessary. Data from epidemiologic studies, of sufficient
quality, are generally preferred for estimating risks. When animal
studies are the basis of the analysis, the estimation of a human-
equivalent dose should utilize toxicokinetic data to inform cross-
species dose scaling if appropriate and if adequate data are available.
Otherwise, default procedures should be applied. For oral dose, based
on current science, an appropriate default option is to scale daily
applied doses experienced for a lifetime in proportion to body weight
raised to the \3/4\ power (U.S. EPA, 1992b). For inhalation dose, based
on current science, an appropriate default methodology estimates
respiratory deposition of particles and gases and estimates internal
doses of gases with different absorption characteristics. When
toxicokinetic modeling (see Section 3.1.2) is used without
toxicodynamic modeling (see Section 3.2.2), the dose-response
assessment develops and supports an approach for addressing
toxicodynamic equivalence, perhaps by retaining some of the cross-
species scaling factor (see Section 3.1.3). Guidance is also provided
for adjustment of dose from adults to children (see Section 4.3.1).
---------------------------------------------------------------------------
\4\ A ``point of departure'' (POD) marks the beginning of
extrapolation to lower doses. The POD is an estimated dose (usually
expressed in human-equivalent terms) near the lower end of the
observed range, without significant extrapolation to lower doses.
---------------------------------------------------------------------------
Response data on effects of the agent on carcinogenic processes are
analyzed (nontumor data) in addition to data on tumor incidence. If
appropriate, the analyses of data on tumor incidence and on precursor
effects may be used in combination. To the extent the relationship
between precursor effects and tumor incidence are known, precursor data
may be used to estimate a dose-response function below the observable
tumor data. Study of the dose-response function for effects
[[Page 17773]]
believed to be part of the carcinogenic process influenced by the agent
may also assist in evaluating the relationship of exposure and response
in the range of observation and at exposure levels below the range of
observation.
The first step of dose-response assessment is evaluation within the
range of observation. Approaches to analysis of the range of
observation of epidemiologic studies are determined by the type of
study and how dose and response are measured in the study. In the
absence of adequate human data for dose-response analysis, animal data
are generally used. If there are sufficient quantitative data and
adequate understanding of the carcinogenic process, a biologically
based model may be developed to relate dose and response data on an
agent-specific basis. Otherwise, as a default procedure, a standard
model can be used to curve-fit the data.
The POD for extrapolating the relationship to environmental
exposure levels of interest, when the latter are outside the range of
observed data, is generally the lower 95% confidence limit on the
lowest dose level that can be supported for modeling by the data. SAB
(1997) suggested that, ``it may be appropriate to emphasize lower
statistical bounds in screening analyses and in activities designed to
develop an appropriate human exposure value, since such activities
require accounting for various types of uncertainties and a lower bound
on the central estimate is a scientifically-based approach accounting
for the uncertainty in the true value of the ED10 [or
central estimate].'' However, the consensus of the SAB (1997) was that,
``both point estimates and statistical bounds can be useful in
different circumstances, and recommended that the Agency routinely
calculate and present the point estimate of the ED10 [or
central estimate] and the corresponding upper and lower 95% statistical
bounds.'' For example, it may be appropriate to emphasize the central
estimate in activities that involve formal uncertainty analysis that
are required by OMB Circular A-4 (OMB, 2003) as well as ranking agents
as to their carcinogenic hazard. Thus, risk assessors should calculate,
to the extent practicable, and present the central estimate and the
corresponding upper and lower statistical bounds (such as confidence
limits) to inform decisionmakers.
The second step of dose-response assessment is extrapolation to
lower dose levels, if needed. This extrapolation is based on extension
of a biologically based model if supported by substantial data (see
Section 3.3.2). Otherwise, default approaches can be applied that are
consistent with current understanding of mode(s) of action of the
agent, including approaches that assume linearity or nonlinearity of
the dose-response relationship, or both. A default approach for
linearity extends a straight line from the POD to zero dose/zero
response (see Section 3.3.3). The linear approach is used when: (1)
There is an absence of sufficient information on modes of action or (2)
the mode of action information indicates that the dose-response curve
at low dose is or is expected to be linear. Where alternative
approaches have significant biological support, and no scientific
consensus favors a single approach, an assessment may present results
using alternative approaches. A nonlinear approach can be used to
develop a reference dose or a reference concentration (see Section
3.3.4).
1.3.5. Susceptible Populations and Lifestages
An important use of mode of action information is to identify
susceptible populations and lifestages. It is rare to have
epidemiologic studies or animal bioassays conducted in susceptible
individuals. This information need can be filled by identifying the key
events of the mode of action and then identifying risk factors, such as
differences due to genetic polymorphisms, disease, altered organ
function, lifestyle, and lifestage, that can augment these key events.
To do this, the information about the key precursor events is reviewed
to identify particular populations or lifestages that can be
particularly susceptible to their occurrence (see Section 2.4.3.4). Any
information suggesting quantitative differences between populations or
lifestages is flagged for consideration in the dose-response assessment
(see Section 3.5 and U.S. EPA 2002b).
1.3.6. Evaluating Risks From Childhood Exposures
NRC (1994) recommended that ``EPA should assess risks to infants
and children whenever it appears that their risks might be greater than
those of adults.'' Executive Order 13045 (1997) requires that ``each
Federal Agency shall make it a high priority to identify and assess
environmental health and safety risks that may disproportionately
affect children, and shall ensure that their policies, programs, and
standards address disproportionate risks that result from environmental
health risks or safety risks.'' In assessing risks to children, EPA
considers both effects manifest during childhood and early-life
exposures that can contribute to effects at any time later in life.
These cancer guidelines view childhood as a sequence of lifestages
rather than viewing children as a subpopulation, the distinction being
that a subpopulation refers to a portion of the population, whereas a
lifestage is inclusive of the entire population. Exposures that are of
concern extend from conception through adolescence and also include
pre-conception exposures of both parents. These cancer guidelines use
the term ``childhood'' in this more inclusive sense.
Rarely are there studies that directly evaluate risks following
early-life exposure. Epidemiologic studies of early-life exposure to
environmental agents are seldom available. Standard animal bioassays
generally begin dosing after the animals are several weeks old, when
many organ systems are mature. This could lead to an understatement of
risk, because an accepted concept in the science of carcinogenesis is
that young animals are usually more susceptible to the carcinogenic
activity of a chemical than are mature animals (McConnell, 1992).
At this time, there is some evidence of higher cancer risks
following early-life exposure. For radiation carcinogenesis, data
indicate that risks for several forms of cancer are highest following
childhood exposure (NRC, 1990; Miller, 1995; U.S. EPA, 1999c). These
human results are supported by the few animal bioassays that include
perinatal (prenatal or early postnatal) exposure. Perinatal exposure to
some agents can induce higher incidences of the tumors seen in standard
bioassays; some examples include vinyl chloride (Maltoni et al., 1981),
diethylnitrosamine (Peto et al., 1984), benzidine, DDT, dieldrin, and
safrole (Vesselinovitch et al., 1979). Moreover, perinatal exposure to
some agents, including vinyl chloride (Maltoni et al., 1981) and
saccharin (Cohen, 1995; Whysner and Williams, 1996), can induce
different tumors that are not seen in standard bioassays. Surveys
comparing perinatal carcinogenesis bioassays with standard bioassays
for a limited number of chemicals (McConnell, 1992; U.S. EPA, 1996b)
have concluded that
The same tumor sites are usually observed following either
perinatal or adult exposure, and
Perinatal exposure in conjunction with adult exposure
usually increases the incidence of tumors or reduces the latent period
before tumors are observed.
The risk attributable to early-life exposure often appears modest
compared with the risk from lifetime exposure, but it can be about 10-
fold
[[Page 17774]]
higher than the risk from an exposure of similar duration occurring
later in life (Ginsberg, 2003). Further research is warranted to
investigate the extent to which these findings apply to specific
agents, chemical classes, and modes of action or in general.
These empirical results are consistent with current understanding
of the biological processes involved in carcinogenesis, which leads to
a reasonable expectation that children can be more susceptible to many
carcinogenic agents (Anderson et al., 2000; Birnbaum and Fenton, 2003;
Ginsberg, 2003; Miller et al., 2002; Scheuplein et al., 2002). Some
aspects potentially leading to childhood susceptibility are listed
below.
Differences in the capacity to metabolize and clear
chemicals can result in larger or smaller internal doses of the active
agent(s).
More frequent cell division during development can result
in enhanced expression of mutations due to the reduced time available
for repair of DNA lesions (Slikker et al., 2004).
Some embryonic cells, such as brain cells, lack key DNA
repair enzymes.
More frequent cell division during development can result
in clonal expansion of cells with mutations from prior unrepaired DNA
damage (Slikker et al., 2004).
Some components of the immune system are not fully
functional during development (Holladay and Smialowicz, 2000; Holsapple
et al., 2003).
Hormonal systems operate at different levels during
different lifestages.
Induction of developmental abnormalities can result in a
predisposition to carcinogenic effects later in life (Anderson et al.,
2000; Birnbaum and Fenton, 2003; Fenton and Davis, 2002).
To evaluate risks from early-life exposure, these cancer guidelines
emphasize the role of toxicokinetic information to estimate levels of
the active agent in children and toxicodynamic information to identify
whether any key events of the mode of action are of increased concern
early in life. Developmental toxicity studies can provide information
on critical periods of exposure for particular targets of toxicity.
An approach to assessing risks from early-life exposure is
presented in Figure 1-1. In the hazard assessment, when there are mode
of action data, the assessment considers whether these data have
special relevance during childhood, considering the various aspects of
development listed above. Examples of such data include toxicokinetics
that predict a sufficiently large internal dose in children or a mode
of action where a key precursor event is more likely to occur during
childhood. There is no recommended default to settle the question of
whether tumors arising through a mode of action are relevant during
childhood; and adequate understanding the mode of action implies that
there are sufficient data (on either the specific agent or the general
mode of action) to form a confident conclusion about relevance during
childhood (see Section 2.4.3.4).
In the dose-response assessment, the potential for susceptibility
during childhood warrants explicit consideration in each assessment.
These cancer guidelines encourage developing separate risk estimates
for children according to a tiered approach that considers what
pertinent data are available (see Section 3.5). Childhood may be a
susceptible period; moreover, exposures during childhood generally are
not equivalent to exposures at other times and may be treated
differently from exposures occurring later in life (see Section 3.5).
In addition, adjustment of unit risk estimates may be warranted when
used to estimate risks from childhood exposure (see Section 4.4).
At this time, several limitations preclude a full assessment of
children's risk. There are no generally used testing protocols to
identify potential environmental causes of cancers that are unique to
children, including several forms of childhood cancer and cancers that
develop from parental exposures, and cases where developmental exposure
may alter susceptibility to carcinogen exposure in the adult (Birnbaum
and Fenton, 2003). Dose-response assessment is limited by an inability
to observe how developmental exposure can modify incidence and latency
and an inability to estimate the ultimate tumor response resulting from
induced susceptibility to later carcinogen exposures.
To partially address the limitations identified above, EPA
developed in conjunction with these cancer guidelines, Supplemental
Guidance for Assessing Susceptibility from Early-Life Exposure to
Carcinogens (``Supplemental Guidance''). The Supplemental Guidance
addresses a number of issues pertaining to cancer risks associated with
early-life exposures generally, but provides specific guidance on
procedures for adjusting cancer potency estimates only for carcinogens
acting through a mutagenic mode of action. This Supplemental Guidance
recommends, for such chemicals when no chemical-specific data exist, a
default approach using estimates from chronic studies (i.e., cancer
slope factors) with appropriate modifications to address the potential
for differential risk of early-lifestage exposure.
The Agency considered both the advantages and disadvantages to
extending the recommended, age dependent adjustment factors for
carcinogenic potency to carcinogenic agents for which the mode of
action remains unknown. EPA decided to recommend these factors only for
carcinogens acting through a mutagenic mode of action based on a
combination of analysis of available data and long-standing science
policy positions which govern the Agency's overall approach to
carcinogen risk assessment. In general, the Agency prefers to rely on
analyses of data, rather than general defaults. When data are available
for a sensitive lifestage, they would be used directly to evaluate
risks for that chemical and that lifestage on a case-by-case basis. In
the case of nonmutagenic carcinogens, when the mode of action is
unknown, the data were judged by EPA to be too limited and the modes of
action too diverse to use this as a category for which a general
default adjustment factor approach can be applied. In this situation, a
linear low-dose extrapolation methodology (without further adjustment)
is recommended. It is the Agency's long-standing science policy
position that use of the linear low-dose extrapolation approach
provides adequate public health conservatism in the absence of
chemical-specific data indicating differential early-life sensitivity
or when the mode of action is not mutagenic.
The Agency expects to produce additional supplemental guidance for
other modes of action, as data from new research and toxicity testing
indicate it is warranted. EPA intends to focus its research, and work
collaboratively with its federal partners, to improve understanding of
the implications of early life exposure to carcinogens. Development of
guidance for estrogenic agents and chemicals acting through other
processes resulting in endocrine disruption and subsequent
carcinogenesis, for example, might be a reasonable priority in light of
the human experience with diethylstilbesterol and the existing early
life animal studies. It is worth noting that each mode of action for
endocrine disruption will probably require separate analysis.
As the Agency examines additional carcinogenic agents, the age
groupings may differ from those recommended for
[[Page 17775]]
assessing cancer risks from early-life exposure to chemicals with a
mutagenic mode of action. Puberty and its associated biological
changes, for example, involve many biological processes that could lead
to changes in sensitivity to the effects of some carcinogens, depending
on their mode of action. The Agency is interested in identifying
lifestages that may be particularly sensitive or refractory for
carcinogenesis, and believes that the mode of action framework
described in these cancer guidelines is an appropriate mechanism for
elucidating these lifestages. For each additional mode of action
evaluated, the various age groupings determined to be at differential
risk may differ from those proposed in the Supplemental Guidance. For
example, the age groupings selected for the age-dependent adjustments
for carcinogens acting through a mutagenic mode of action were
initially selected based on the available data, i.e., for the
laboratory animal age range representative of birth to < 2 years in
humans. More limited data and information on human biology were used to
determine a science-informed policy regarding 2 to < 16 years. Data
were not available to refine the latter age group. If more data become
available regarding carcinogens with a mutagenic mode of action,
consideration may be given to further refinement of these age groups.
1.3.7. Emphasis on Characterization
The cancer guidelines emphasize the importance of a clear and
useful characterization narrative that summarizes the analyses of
hazard, dose-response, and exposure assessment. These characterizations
summarize the assessments to explain the extent and weight of evidence,
major points of interpretation and rationale for their selection,
strengths and weaknesses of the evidence and the analysis, and discuss
alternative conclusions and uncertainties that deserve serious
consideration (U.S. EPA, 2000b). They serve as starting materials for
the overall risk characterization process that completes the risk
assessment.
BILLING CODE 6560-50-P
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[GRAPHIC] [TIFF OMITTED] TN07AP05.000
BILLING CODE 6560-50-C
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2. Hazard Assessment
2.1. Overview of Hazard Assessment and Characterization
2.1.1. Analyses of Data
The purpose of hazard assessment is to review and evaluate data
pertinent to two questions: (1) Whether an agent may pose a
carcinogenic hazard to human beings, and (2) under what circumstances
an identified hazard may be expressed (NRC, 1994). Hazard assessment
involves analyses of a variety of data that may range from observations
of tumor responses to analysis of structure-activity relationships
(SARs). The purpose of the assessment is not simply to assemble these
separate evaluations; its purpose is to construct a total analysis
examining what the biological data reveal as a whole about carcinogenic
effects and mode of action of the agent, and their implications for
human hazard and dose-response evaluation. Conclusions are drawn from
weight-of-evidence evaluations based on the combined strength and
coherence of inferences appropriately drawn from all of the available
information. To the extent that data permit, hazard assessment
addresses the question of mode of action of an agent as both an initial
step in identifying human hazard potential and as a component in
considering appropriate approaches to dose-response assessment.
The topics in this chapter include analysis of tumor data, both
human and animal, and analysis of other key information about
properties and effects that relate to carcinogenic potential. The
chapter addresses how information can be used to evaluate potential
modes of action. It also provides guidance on performing a weight of
evidence evaluation.
2.1.2. Presentation of Results
Presentation of the results of hazard assessment should be informed
by Agency guidance as discussed in Section 2.6. The results are
presented in a technical hazard characterization that serves as a
support to later risk characterization. It includes:
A summary of the evaluations of hazard data,
The rationales for its conclusions, and
An explanation of the significant strengths or limitations
of the conclusions.
Another presentation feature is the use of a weight of evidence
narrative that includes both a conclusion about the weight of evidence
of carcinogenic potential and a summary of the data on which the
conclusion rests. This narrative is a brief summary that in toto
replaces the alphanumerical classification system used in EPA's 1986
cancer guidelines (U.S. EPA, 1986a).
2.2. Analysis of Tumor Data
Evidence of carcinogenicity comes from finding tumor increases in
humans or laboratory animals exposed to a given agent or from finding
tumors following exposure to structural analogues to the compound under
review. The significance of observed or anticipated tumor effects is
evaluated in reference to all the other key data on the agent. This
section contains guidance for analyzing human and animal studies to
decide whether there is an association between exposure to an agent or
a structural analogue and occurrence of tumors. Note that the use of
the term ``tumor'' in these cancer guidelines is defined as malignant
neoplasms or a combination of malignant and corresponding benign
neoplasms.
Observation of only benign neoplasia may or may not have
significance for evaluation under these cancer guidelines. Benign
tumors that are not observed to progress to malignancy are assessed on
a case-by-case basis. There is a range of possibilities for their
overall significance. They may deserve attention because they are
serious health problems even though they are not malignant; for
instance, benign tumors may be a health risk because of their effect on
the function of a target tissue such as the brain. They may be
significant indicators of the need for further testing of an agent if
they are observed in a short-term test protocol, or such an observation
may add to the overall weight of evidence if the same agent causes
malignancies in a long-term study. Knowledge of the mode of action
associated with a benign tumor response may aid in the interpretation
of other tumor responses associated with the same agent. In other
cases, observation of a benign tumor response alone may have no
significant health hazard implications when other sources of evidence
show no suggestion of carcinogenicity.
2.2.1. Human Data
Human data may come from epidemiologic studies or case reports.
(Clinical human studies, which involve intentional exposures to
substances, may provide toxicokinetic data, but generally not data on
carcinogenicity.) The most common sources of human data for cancer risk
assessment are epidemiologic investigations. Epidemiology is the study
of the distribution of disease in human populations and the factors
that may influence that distribution. The goals of cancer epidemiology
are to identify distribution of cancer risk and determine the extent to
which the risk can be attributed causally to specific exposures to
exogenous or endogenous factors (see Centers for Disease Control and
Prevention [CDC, 2004]). Epidemiologic data are extremely valuable in
risk assessment because they provide direct evidence on whether a
substance is likely to produce cancer in humans, thereby avoiding
issues such as: species-to-species inference, extrapolation to
exposures relevant to people, effects of concomitant exposures due to
lifestyles. Thus, epidemiologic studies typically evaluate agents under
more relevant conditions. When human data of high quality and adequate
statistical power are available, they are generally preferable over
animal data and should be given greater weight in hazard
characterization and dose-response assessment, although both can be
used.
Null results from epidemiologic studies alone generally do not
prove the absence of carcinogenic effects because such results can
arise either from an agent being truly not carcinogenic or from other
factors such as: inadequate statistical power, inadequate study design,
imprecise estimates, or confounding factors. Moreover, null results
from a well-designed and well-conducted epidemiologic study that
contains usable exposure data can help to define upper limits for the
estimated dose of concern for human exposure in cases where the overall
weight of the evidence indicates that the agent is potentially
carcinogenic in humans. Furthermore, data from a well designed and well
conducted epidemiologic study that does not show positive results, in
conjunction with compelling mechanistic information, can lend support
to a conclusion that animal responses may not be predictive of a human
cancer hazard.
Epidemiology can also complement experimental evidence in
corroborating or clarifying the carcinogenic potential of the agent in
question. For example, epidemiologic studies that show elevated cancer
risk for tumor sites corresponding to those at which laboratory animals
experience increased tumor incidence can strengthen the weight of
evidence of human carcinogenicity. Furthermore, biochemical or
molecular epidemiology may help improve understanding of the mechanisms
of human carcinogenesis.
[[Page 17778]]
2.2.1.1. Assessment of Evidence of Carcinogenicity From Human Data
All studies that are considered to be of acceptable quality,
whether yielding positive or null results, or even suggesting
protective carcinogenic effects, should be considered in assessing the
totality of the human evidence. Conclusions about the overall evidence
for carcinogenicity from available studies in humans should be
summarized along with a discussion of uncertainties and gaps in
knowledge. Conclusions regarding the strength of the evidence for
positive or negative associations observed, as well as evidence
supporting judgments of causality, should be clearly described. In
assessing the human data within the overall weight of evidence,
determination about the strength of the epidemiologic evidence should
clearly identify the degree to which the observed associations may be
explained by other factors, including bias or confounding.
Characteristics that are generally desirable in epidemiologic
studies include (1) Clear articulation of study objectives or
hypothesis; (2) proper selection and characterization of comparison
groups (exposed and unexposed groups or case and control groups); (3)
adequate characterization of exposure; (4) sufficient length of follow-
up for disease occurrence; (5) valid ascertainment of the causes of
cancer morbidity and mortality; (6) proper consideration of bias and
confounding factors; (7) adequate sample size to detect an effect; (8)
clear, well-documented, and appropriate methodology for data collection
and analysis; (9) adequate response rate and methodology for handling
missing data; and (10) complete and clear documentation of results. No
single criterion determines the overall adequacy of a study. Practical
and resource constraints may limit the ability to address all of these
characteristics in a study. The risk assessor is encouraged to consider
how the limitations of the available studies might influence the
conclusions. While positive biases may be due, for example, to a
healthy worker effect, it is also important to consider negative
biases, for example, workers who may leave the workforce due to illness
caused either by high exposures to the agent or to effects of
confounders such as smoking. The following discussions highlight the
major factors included in an analysis of epidemiologic studies.
2.2.1.2. Types of Studies
The major types of cancer epidemiologic study designs used for
examining environmental causes of cancer are analytical studies and
descriptive studies. Each study type has well-known strengths and
weaknesses that affect interpretation of results, as summarized below
(Lilienfeld and Lilienfeld, 1979; Mausner and Kramer, 1985; Kelsey et
al., 1996; Rothman and Greenland, 1998).
Analytical epidemiologic studies, which include case-control and
cohort designs, are generally relied on for identifying a causal
association between human exposure and adverse health effects. In case-
control studies, groups of individuals with (cases) and without
(controls) a particular disease are identified and compared to
determine differences in exposure. In cohort studies, a group of
``exposed'' and ``nonexposed'' individuals are identified and studied
over time to determine differences in disease occurrence. Cohort
studies can be performed either prospectively or retrospectively from
historical records. The type of study chosen may depend on the
hypothesis to be evaluated. For example, case-control studies may be
more appropriate for rare cancers while cohort studies may be more
appropriate for more commonly occurring cancers.
On the other hand, descriptive epidemiologic studies examine
symptom or disease rates among populations in relation to personal
characteristics such as age, gender, race, and temporal or
environmental conditions. Descriptive studies are most frequently used
to generate hypotheses about exposure factors, but subsequent
analytical designs are necessary to infer causality. For example,
cross-sectional designs might be used to compare the prevalence of
cancer between areas near and far from a Superfund site. However, in
studies where exposure and disease information applies only to the
current conditions, it is not possible to infer that the exposure
actually caused the disease. Therefore, these studies are used to
identify patterns or trends in disease occurrence over time or in
different geographical locations, but typical limitations in the
characterization of populations in these studies make it difficult to
infer the causal agent or degree of exposure.
Case reports describe a particular effect in an individual or group
of individuals who were exposed to a substance. These reports are often
anecdotal or highly selective in nature and generally are of limited
use for hazard assessment. Specifically, cancer causality can rarely be
inferred from case reports alone. Investigative follow-up may or may
not accompany such reports. For cancer, the most common types of case
series are associated with occupational and childhood exposures. Case
reports can be particularly valuable for identifying unique features,
such as an association with an uncommon tumor (e.g., inhalation of
vinyl chloride and hepatic angiosarcoma in workers or ingestion of
diethylstilbestrol by mothers and clear-cell carcinoma of the vagina in
offspring).
2.2.1.3. Exposure Issues
For epidemiologic data to be useful in determining whether there is
an association between health effects and exposure to an agent, there
should be adequate characterization of exposure information. In
general, greater weight should be given to studies with more precise
and specific exposure estimates.
Questions to address about exposure are: What can one reliably
conclude about the exposure parameters including (but not limited to)
the level, duration, route, and frequency of exposure of individuals in
one population as compared with another? How sensitive are study
results to uncertainties in these parameters?
Actual exposure measurements are not available for many
retrospective studies. Therefore, surrogates are often used to
reconstruct exposure parameters. These may involve attributing
exposures to job classifications in a workplace or to broader
occupational or geographic groupings. Use of surrogates carries a
potential for misclassification, i.e., individuals may be placed in an
incorrect exposure group. Misclassification generally leads to reduced
ability of a study to detect differences between study and referent
populations.
When either current or historical monitoring data are available,
the exposure evaluation includes consideration of the error bounds of
the monitoring and analytic methods and whether the data are from
routine or accidental exposures. The potential for misclassification
and for measurement errors is amenable to both qualitative and
quantitative analysis. These are essential analyses for judging a
study's results, because exposure estimation is the most critical part
of a retrospective study.
2.2.1.4. Biological Markers
Biological markers potentially offer excellent measures of exposure
(Hulka and Margolin, 1992; Peto and Darby, 1994). In some cases,
molecular or
[[Page 17779]]
cellular effects (e.g., DNA or protein adducts, mutation, chromosomal
aberrations, levels of thyroid-stimulating hormone) can be measured in
blood, body fluids, cells, and tissues to serve as biomarkers of
exposure in humans and animals (Callemen et al., 1978; Birner et al.,
1990). As such, they can act as an internal surrogate measure of
chemical dose, representing, as appropriate, either recent exposure
(e.g., serum concentration) or accumulated exposure over some period
(e.g., hemoglobin adducts). Validated markers of exposure such as
alkylated hemoglobin from exposure to ethylene oxide (Van Sittert et
al., 1985) or urinary arsenic (Enterline et al., 1987) can improve
estimates of dose over the relevant time periods for the markers.
Markers closely identified with effects promise to greatly increase the
ability of studies to distinguish real effects from bias at low levels
of relative risk between populations (Taylor et al., 1994; Biggs et
al., 1993) and to resolve problems of confounding risk factors.
However, when using molecular or cellular effects as biomarkers of
exposure, since many of these changes are often not specific to just
one type of exposure, it is important to be aware that changes may be
due to exposures unrelated to the exposure of interest and attention
must be paid to controlling for potential confounders.
Biochemical or molecular epidemiologic studies may use biological
markers of effect as indicators of disease or its precursors. The
application of techniques for measuring cellular and molecular
alterations due to exposure to specific environmental agents may allow
conclusions to be drawn about the mechanisms of carcinogenesis (see
section 2.4 for more information on this topic).
2.2.1.5. Confounding Factors
Control for potential confounding factors is an important
consideration in the evaluation of the design and in the analysis of
observational epidemiologic studies. A confounder is a variable that is
related to both the health outcome of concern (cancer) and exposure.
Common examples include age, socioeconomic status, smoking habits, and
diet. For instance, if older people are more likely to be exposed to a
given contaminant as well as more likely to have cancer because of
their age, age is considered a confounder. Adjustment for potentially
confounding factors (from a statistical as contrasted with an
epidemiologic point of view) can occur either in the design of the
study (e.g., individual or group matching on critical factors) or in
the statistical analysis of the results (stratification or direct or
indirect adjustment). Direct adjustment in the statistical analysis may
not be possible owing to the presentation of the data or because needed
information was not collected during the study. In this case, indirect
comparisons may be possible. For example, in the absence of data on
smoking status among individuals in the study population, an
examination of the possible contribution of cigarette smoking to
increased lung cancer risk may be based on information from other
sources, such as the American Cancer Society's longitudinal studies
(Hammand, 1966; Garfinkel and Silverberg, 1991). The effectiveness of
adjustments contributes to the ability to draw inferences from a study.
Different studies involving exposure to an agent may have different
confounding factors. If consistent increases in cancer risk are
observed across a collection of studies with different confounding
factors, the inference that the agent under investigation was the
etiologic factor is strengthened.
There may also be instances where the agent of interest is a risk
factor in conjunction with another agent. For instance, interaction as
well as effect-measure modification are sometimes construed to be
confounding, but they are different than confounding. Interaction is
described as a situation in which two or more risk factors modify the
effect of each other with regard to the occurrence of a given effect.
This phenomenon is sometimes described as effect-measure modification
or heterogeneity of effect (Szklo and Nieto, 2000). Effect-measure
modification refers to variation in the magnitude of measure exposure
effect across levels of another variable (Rothman and Greenland, 1998).
The variable across which the effect measure varies and is called an
effect modifier (e.g., hepatitis virus B and aflatoxin in hepatic
cancer). Interaction, on the other hand, means effect of the exposure
on the outcome differs, depending on the presence of another variable
(the effect modifier). When the effect of the exposure of interest is
accentuated by another variable, it is said to be synergistic
interaction. Synergistic interaction can be additive (e.g., hepatitis
virus B and aflatoxin in hepatic cancer) or multiplicative (e.g.,
asbestos and smoking in lung cancer). If the effect of exposure is
diminished or eliminated by another variable, it said to be
antagonistic interaction (e.g., intake of vitamin E and lower
occurrence of lung cancer).
2.2.1.6. Statistical Considerations
The analysis should apply appropriate statistical methods to
ascertain whether the observed association between exposure and effects
would be expected by chance. A description of the method or methods
used should include the reasons for their selection. Statistical
analyses of the bias, confounding, and interaction are part of
addressing the significance of an association and the power of a study
to detect an effect.
The analysis augments examination of the results for the whole
population with exploration of the results for groups with
comparatively greater exposure or time since first exposure. This may
support identifying an association or establishing a dose-response
trend. When studies show no association, such exploration may apply to
determining an upper limit on potential human risk for consideration
alongside results of animal tumor effects studies.
2.2.1.6.1. Likelihood of Observing an Effect
The power of a study--the likelihood of observing an effect if one
exists--increases with sample size, i.e., the number of subjects
studied from a population. (For example, a quadrupling of a background
rate in the 1 per 10,000 range would require more subjects who have
experienced greater or longer exposure or lengthier follow-up, than a
doubling of a background rate in the 1 per 100 range.) If the size of
the effect is expected to be very small at low doses, higher doses or
longer durations of exposure may be needed to have an appreciable
likelihood of observing an effect with a given sample size. Because of
the often long latency period in cancer development, the likelihood of
observing an effect also depends on whether adequate time has elapsed
since exposure began for effects to occur. Since the design of the
study and the choice of analysis, as well as the design level of
certainty in the results and the magnitude of response in an unexposed
population also affect the likelihood of observing an effect, it is
important to carefully interpret the absence of an observed effect. A
unique feature that can be ascribed to the effects of a particular
agent (such as a tumor type that is seen only rarely in the absence of
the agent) can increase sensitivity by permitting separation of bias
and confounding factors from real effects. Similarly, a biomarker
particular to the agent can permit these distinctions. Statistical re-
analyses of data, particularly an examination of
[[Page 17780]]
different exposure indices, can give insight into potential exposure-
response relationships. These are all factors to explore in statistical
analysis of the data.
2.2.1.6.2. Sampling and Other Bias Issues
When comparing cases and controls or exposed and non-exposed
populations, it would be preferable for the two populations to differ
only in exposure to the agent in question. Because this is seldom the
case, it is important to identify sources of sampling and other
potential biases inherent in a study design or data collection methods.
Bias is a systematic error. In epidemiologic studies, bias can
occur in the selection of cases and controls or exposed and non-exposed
populations, as well as the follow up of the groups, or the
classification of disease or exposure. The size of the risks observed
can be affected by noncomparability between populations of factors such
as general health, diet, lifestyle, or geographic location; differences
in the way case and control individuals recall past events; differences
in data collection that result in unequal ascertainment of health
effects in the populations; and unequal follow-up of individuals
(Rothman and Greenland, 1998). Other factors worth consideration can be
inherent in the available cohorts, e.g., use of occupational studies
(the healthy worker effect), absence of one sex, or limitations in
sample size for one or more ethnicities.
The mere presence of biases does not invalidate a study, but should
be reflected in the judgment of its strengths or weaknesses. Acceptance
of studies for assessment depends on identifying their sources of bias
and the possible effects on study results.
2.2.1.6.3. Combining Statistical Evidence Across Studies
Meta-analysis is a means of integrating the results of multiple
studies of similar health effects and risk factors. This technique is
particularly useful when various studies yield varying degrees of risk
or even conflicting associations (negative and positive). It is
intended to introduce consistency and comprehensiveness into what
otherwise might be a more subjective review of the literature. The
value of such an analysis is dependent upon a systematic review of the
literature that uses transparent criteria of inclusion and exclusion.
In interpreting such analyses, it is important to consider the effects
of differences in study quality, as well as the effect of publication
bias. Meta-analysis may not be advantageous in some circumstances.
These include when the relationship between exposure and disease is
obvious from the individual studies; when there are only a few studies
of the key health outcomes; when there is insufficient information from
available studies related to disease, risk estimate, or exposure
classification to insure comparability; or when there are substantial
confounding or other biases that cannot be adjusted for in the analysis
(Blair et al., 1995; Greenland, 1987; Peto, 1992).
2.2.1.7. Evidence for Causality
Determining whether an observed association (risk) is causal rather
than spurious involves consideration of a number of factors. Sir
Bradford Hill (Hill, 1965) developed a set of guidelines for evaluating
epidemiologic associations that can be used in conjunction with the
discussion of causality such as the 2004 Surgeon General's report on
smoking (CDC, 2004) and in other documents (e.g., Rothman and Greenland
1998; IPCS, 1999). The critical assessment of epidemiologic evidence is
conceptually based upon consideration of salient aspects of the
evidence of associations so as to reach fundamental judgments as to the
likely causal significance of the observed associations. In so doing,
it is appropriate to draw from those aspects initially presented in
Hill's classic monograph (Hill, 1965) and widely used by the scientific
community in conducting such evidence-based reviews. A number of these
aspects are judged to be particularly salient in evaluating the body of
evidence available in this review, including the aspects described by
Hill as strength, experiment, consistency, plausibility, and coherence.
Other aspects identified by Hill, including temporality and biological
gradient, are also relevant and considered here (e.g., in
characterizing lag structures and concentration-response
relationships), but are more directly addressed in the design and
analyses of the individual epidemiologic studies included in this
assessment. As discussed below, these salient aspects are interrelated
and considered throughout the evaluation of the epidemiologic evidence
generally reflected in the integrative synthesis of the mode of action
framework.
The general evaluation of the strength of the epidemiological
evidence reflects consideration not only of the magnitude of reported
effects estimates and their statistical significance, but also of the
precision of the effects estimates and the robustness of the effects
associations. Consideration of the robustness of the associations takes
into account a number of factors, including in particular the impact of
alternative models and model specifications and potential confounding
factors, as well issues related to the consequences of measurement
error. Consideration of the consistency of the effects associations
involves looking across the results of studies conducted by different
investigators in different places and times. Particular weight may be
given, consistent with Hill's views, to the presence of ``similar
results reached in quite different ways, e.g., prospectively and
retrospectively'' (Hill, 1965). Looking beyond the epidemiological
evidence, evaluation of the biological plausibility of the associations
observed in epidemiologic studies reflects consideration of both
exposure-related factors and toxicological evidence relevant to
identification of potential modes of action (MOAs). Similarly,
consideration of the coherence of health effects associations reported
in the epidemiologic literature reflects broad consideration of
information pertaining to the nature of the biological markers
evaluated in toxicologic and epidemiologic studies.
In identifying these aspects as being particularly salient in this
assessment, it is also important to recognize that no one aspect is
either necessary or sufficient for drawing inferences of causality. As
Hill (1965) emphasized:
None of my nine viewpoints can bring indisputable evidence for
or against the cause-and-effect hypothesis and none can be required
as a sine qua non. What they can do, with greater or less strength,
is to help us to make up our minds on the fundamental question--is
there any other way of explaining the set of facts before us, is
there any other answer equally, or more, likely than cause and
effect?
While these aspects frame considerations weighed in assessing the
epidemiologic evidence, they do not lend themselves to being considered
in terms of simple formulas or hard-and-fast rules of evidence leading
to answers about causality (Hill, 1965). One, for example, cannot
simply count up the numbers of studies reporting statistically
significant results or statistically non-significant results for
carcinogenesis and related MOAs and reach credible conclusions about
the relative strength of the evidence and the likelihood of causality.
Rather, these important considerations are taken into account
throughout the assessment with a goal of producing an objective
appraisal of the evidence (informed by peer and public comment and
advice),
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which includes the weighing of alternative views on controversial
issues. Thus, although these guidelines have become known as ``causal
criteria,'' it is important to note that they cannot be used as a
strictly quantitative checklist. Rather, these ``criteria'' should be
used to determine the strength of the evidence for concluding
causality. In particular, the absence of one or more of the
``criteria'' does not automatically exclude a study from consideration
(e.g., see discussion in CDC, 2004). The list below has been adapted
from Hill's guidelines as an aid in judging causality.
(a) Consistency of the observed association. An inference of
causality is strengthened when a pattern of elevated risks is observed
across several independent studies. The reproducibility of findings
constitutes one of the strongest arguments for causality. If there are
discordant results among investigations, possible reasons such as
differences in exposure, confounding factors, and the power of the
study are considered.
(b) Strength of the observed association. The finding of large,
precise risks increases confidence that the association is not likely
due to chance, bias, or other factors. A modest risk, however, does not
preclude a causal association and may reflect a lower level of
exposure, an agent of lower potency, or a common disease with a high
background level.
(c) Specificity of the observed association. As originally
intended, this refers to increased inference of causality if one cause
is associated with a single effect or disease (Hill, 1965). Based on
our current understanding that many agents cause cancer at multiple
sites, and many cancers have multiple causes, this is now considered
one of the weaker guidelines for causality. Thus, although the presence
of specificity may support causality, its absence does not exclude it.
(d) Temporal relationship of the observed association. A causal
interpretation is strengthened when exposure is known to precede
development of the disease. Because a latent period of up to 20 years
or longer is often associated with cancer development in adults, the
study should consider whether exposures occurred sufficiently long ago
to produce an effect at the time the cancer is assessed. This is among
the strongest criteria for an inference of causality.
(e) Biological gradient (exposure-response relationship). A clear
exposure-response relationship (e.g., increasing effects associated
with greater exposure) strongly suggests cause and effect, especially
when such relationships are also observed for duration of exposure
(e.g., increasing effects observed following longer exposure times).
There are many possible reasons that an epidemiologic study may fail to
detect an exposure-response relationship. For example, an analysis that
included decreasing exposures due to improved technology that is
combined with higher prior exposure in an initial analysis can require
a segmented analysis to apportion exposure. Other reasons for failure
to detect a relationship may include a small range of exposures. Thus,
the absence of an exposure-response relationship does not exclude a
causal relationship.
(f) Biological plausibility. An inference of causality tends to be
strengthened by consistency with data from experimental studies or
other sources demonstrating plausible biological mechanisms. A lack of
mechanistic data, however, is not a reason to reject causality.
(g) Coherence. An inference of causality may be strengthened by
other lines of evidence that support a cause-and-effect interpretation
of the association. Information is considered from animal bioassays,
toxicokinetic studies, and short-term studies. The absence of other
lines of evidence, however, is not a reason to reject causality.
(h) Experimental evidence (from human populations). Experimental
evidence is seldom available from human populations and exists only
when conditions of human exposure have occurred to create a ``natural
experiment'' at different levels of exposure. Strong evidence for
causality can be provided when a change in exposure brings about a
change in disease frequency, for example, the decrease in the risk of
lung cancer that follows cessation of smoking.
(i) Analogy. SARs and information on the agent's structural
analogues can provide insight into whether an association is causal.
Similarly, information on mode of action for a chemical, as one of many
structural analogues, can inform decisions regarding likely causality.
2.2.2. Animal Data
Various whole-animal test systems are currently used or are under
development for evaluating potential carcinogenicity. Cancer studies
involving chronic exposure for most of the lifespan of an animal are
generally accepted for evaluation of tumor effects (Tomatis et al.,
1989; Rall, 1991; Allen et al., 1988; but see Ames and Gold, 1990).
Other studies of special design are useful for observing formation of
preneoplastic lesions or tumors or investigating specific modes of
action. Their applicability is determined on a case-by-case basis.
2.2.2.1. Long-Term Carcinogenicity Studies
The objective of long-term carcinogenesis bioassays is to determine
the potential carcinogenic hazard and dose-response relationships of
the test agent. Carcinogenicity rodent studies are designed to examine
the production of tumors as well as preneoplastic lesions and other
indications of chronic toxicity that may provide evidence of treatment-
related effects and insights into the way the test agent produces
tumors. Current standardized carcinogenicity studies in rodents test at
least 50 animals per sex per dose group in each of three treatment
groups and in a concurrent control group, usually for 18 to 24 months,
depending on the rodent species tested (OECD, 1981; U.S. EPA, 1998c).
The high dose in long-term studies is generally selected to provide the
maximum ability to detect treatment-related carcinogenic effects while
not compromising the outcome of the study through excessive toxicity or
inducing inappropriate toxicokinetics (e.g., overwhelming absorption or
detoxification mechanisms). The purpose of two or more lower doses is
to provide some information on the shape of the dose-response curve.
Similar protocols have been and continue to be used by many
laboratories worldwide.
All available studies of tumor effects in whole animals should be
considered, at least preliminarily. The analysis should discard studies
judged to be wholly inadequate in protocol, conduct, or results.
Criteria for the technical adequacy of animal carcinogenicity studies
have been published and should be used as guidance to judge the
acceptability of individual studies (e.g., NTP, 1984; OSTP, 1985;
Chhabra et al., 1990). As these criteria, in whole or in part, may be
updated by the National Toxicology Program (NTP) and others, the
analyst should consult the appropriate sources to determine both the
current standards as well as those that were contemporaneous with the
study. Care should be taken to include studies that provide some
evidence bearing on carcinogenicity or that help interpret effects
noted in other studies, even if these studies have some limitations of
protocol or conduct. Such limited, but not wholly inadequate, studies
can contribute as their deficiencies permit. The findings of
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long-term rodent bioassays should be interpreted in conjunction with
results of prechronic studies along with toxicokinetic studies and
other pertinent information, if available. Evaluation of tumor effects
takes into consideration both biological and statistical significance
of the findings (Haseman, 1984, 1985, 1990, 1995). The following
sections highlight the major issues in the evaluation of long-term
carcinogenicity studies.
2.2.2.1.1. Dosing Issues
Among the many criteria for technical adequacy of animal
carcinogenicity studies is the appropriateness of dose selection. The
selection of doses for chronic bioassays is based on scientific
judgments and sound toxicologic principles. Dose selection should be
made on the basis of relevant toxicologic information from prechronic,
mechanistic, and toxicokinetic and mechanistic studies. A scientific
rationale for dose selection should be clearly articulated (e.g., NTP,
1984; ILSI, 1997). How well the dose selection is made is evaluated
after the completion of the bioassay.
Interpretation of carcinogenicity study results is profoundly
affected by study exposure conditions, especially by inappropriate dose
selection. This is particularly important in studies that do not show
positive results for carcinogenicity, because failure to use a
sufficiently high dose reduces the sensitivity of the studies. A lack
of tumorigenic responses at exposure levels that cause significant
impairment of animal survival may also not be acceptable. In addition,
overt toxicity or qualitatively altered toxicokinetics due to
excessively high doses may result in tumor effects that are secondary
to the toxicity rather than directly attributable to the agent.
With regard to the appropriateness of the high dose, an adequate
high dose would generally be one that produces some toxic effects
without unduly affecting mortality from effects other than cancer or
producing significant adverse effects on the nutrition and health of
the test animals (OECD, 1981; NRC, 1993a). If the test agent does not
appear to cause any specific target organ toxicity or perturbation of
physiological function, an adequate high dose can be specified in terms
of a percentage reduction of body weight gain over the lifespan of the
animals. The high dose would generally be considered inadequate if
neither toxicity nor change in weight gain is observed. On the other
hand, significant increases in mortality from effects other than cancer
generally indicate that an adequate high dose has been exceeded.
Other signs of treatment-related toxicity associated with an
excessive high dose may include (a) Significant reduction of body
weight gain (e.g., greater than 10%), (b) significant increases in
abnormal behavioral and clinical signs, (c) significant changes in
hematology or clinical chemistry, (d) saturation of absorption and
detoxification mechanisms, or (e) marked changes in organ weight,
morphology, and histopathology. It should be noted that practical upper
limits have been established to avoid the use of excessively high doses
in long-term carcinogenicity studies of environmental chemicals (e.g.,
5% of the test substance in the feed for dietary studies or 1 g/kg body
weight for oral gavage studies [OECD, 1981]).
For dietary studies, weight gain reductions should be evaluated as
to whether there is a palatability problem or an issue with food
efficiency; certainly, the latter is a toxic manifestation. In the case
of inhalation studies with respirable particles, evidence of impairment
of normal clearance of particles from the lung should be considered
along with other signs of toxicity to the respiratory airways to
determine whether the high exposure concentration has been
appropriately selected (U.S. EPA, 2001a). For dermal studies, evidence
of skin irritation may indicate that an adequate high dose has been
reached (U.S. EPA, 1989).
In order to obtain the most relevant information from a long-term
carcinogenicity study, it is important to maximize exposure conditions
to the test material. At the same time, caution is appropriate in using
excessive high-dose levels that would confound the interpretation of
study results to humans. The middle and lowest doses should be selected
to characterize the shape of the dose-response curve as much as
possible. It is important that the doses be adequately spaced so that
the study can provide relevant dose-response data for assessing human
hazard and risk. If the testing of potential carcinogenicity is being
combined with an evaluation of noncancer chronic toxicity, the study
should be designed to include one dose in addition to the control(s)
that is not expected to elicit adverse effects.
There are several possible outcomes regarding the study
interpretation of the significance and relevance of tumorigenic effects
associated with exposure or dose levels below, at, or above an adequate
high dose. The general guidance is given here; for each case, the
information at hand should be evaluated and a rationale should be given
for the position taken.
Adequately high dose. If an adequately high dose has been
used, tumor effects are judged positive or negative depending on the
presence or absence of significant tumor incidence increases,
respectively.
Excessively high dose. If toxicity or mortality is
excessive at the high dose, interpretation depends on whether or not
tumors are found.
--Studies that show tumor effects only at excessive doses may be
compromised and may or may not carry weight, depending on the
interpretation in the context of other study results and other lines of
evidence. Results of such studies, however, are generally not
considered suitable for dose-response extrapolation if it is determined
that the mode(s) of action underlying the tumorigenic responses at high
doses is not operative at lower doses.
--Studies that show tumors at lower doses, even though the high dose is
excessive and may be discounted, should be evaluated on their own
merits.
--If a study does not show an increase in tumor incidence at a toxic
high dose and appropriately spaced lower doses are used without such
toxicity or tumors, the study is generally judged as negative for
carcinogenicity.
Inadequately high dose. Studies of inadequate sensitivity
where an adequately high dose has not been reached may be used to bound
the dose range where carcinogenic effects might be expected.
2.2.2.1.2. Statistical Considerations
The main aim of statistical evaluation is to determine whether
exposure to the test agent is associated with an increase of tumor
development. Statistical analysis of a long-term study should be
performed for each tumor type separately. The incidence of benign and
malignant lesions of the same cell type, usually within a single tissue
or organ, are considered separately but may be combined when
scientifically defensible (McConnell et al., 1986).
Trend tests and pairwise comparison tests are the recommended tests
for determining whether chance, rather than a treatment-related effect,
is a plausible explanation for an apparent increase in tumor incidence.
A trend test such as the Cochran-Armitage test (Snedecor and Cochran,
1967) asks whether the results in all dose groups together increase as
dose increases. A pairwise comparison test such as the
[[Page 17783]]
Fisher exact test (Fisher, 1950) asks whether an incidence in one dose
group is increased over that of the control group. By convention, for
both tests a statistically significant comparison is one for which p is
less than 0.05 that the increased incidence is due to chance.
Significance in either kind of test is sufficient to reject the
hypothesis that chance accounts for the result.
A statistically significant response may or may not be biologically
significant and vice versa. The selection of a significance level is a
policy choice based on a trade-off between the risks of false positives
and false negatives. A result with a significance level of greater or
less than 5% (the most common significance level) is examined to see if
the result confirms other scientific information. When the assessment
departs from a simple 5% level, this should be highlighted in the risk
characterization. A two-tailed test or a one-tailed test can be used.
In either case a rationale is provided.
Statistical power can affect the likelihood that a statistically
significant result could reasonably be expected. This is especially
important in studies or dose groups with small sample sizes or low dose
rates. Reporting the statistical power can be useful for comparing and
reconciling positive and negative results from different studies.
Considerations of multiple comparisons should also be taken into
account. Haseman (1983) analyzed typical animal bioassays that tested
both sexes of two species and concluded that, because of multiple
comparisons, a single tumor increase for a species-sex-site combination
that is statistically significant at the 1% level for common tumors or
5% for rare tumors corresponds to a 7-8% significance level for the
study as a whole. Therefore, animal bioassays presenting only one
significant result that falls short of the 1% level for a common tumor
should be treated with caution.
2.2.2.1.3. Concurrent and Historical Controls
The standard for determining statistical significance of tumor
incidence comes from a comparison of tumors in dosed animals with those
in concurrent control animals. Additional insights about both
statistical and biological significance can come from an examination of
historical control data (Tarone, 1982; Haseman, 1995). Historical
control data can add to the analysis, particularly by enabling
identification of uncommon tumor types or high spontaneous incidence of
a tumor in a given animal strain. Identification of common or uncommon
situations prompts further thought about the meaning of the response in
the current study in context with other observations in animal studies
and with other evidence about the carcinogenic potential of the agent.
These other sources of information may reinforce or weaken the
significance given to the response in the hazard assessment. Caution
should be exercised in simply looking at the ranges of historical
responses, because the range ignores differences in survival of animals
among studies and is related to the number of studies in the database.
In analyzing results for uncommon tumors in a treated group that
are not statistically significant in comparison with concurrent
controls, the analyst may be informed by the experience of historical
controls to conclude that the result is in fact unlikely to be due to
chance. However, caution should be used in interpreting results. In
analyzing results for common tumors, a different set of considerations
comes into play. Generally speaking, statistically significant
increases in tumors should not be discounted simply because incidence
rates in the treated groups are within the range of historical controls
or because incidence rates in the concurrent controls are somewhat
lower than average. Random assignment of animals to groups and proper
statistical procedures provide assurance that statistically significant
results are unlikely to be due to chance alone. However, caution should
be used in interpreting results that are barely statistically
significant or in which incidence rates in concurrent controls are
unusually low in comparison with historical controls.
In cases where there may be reason to discount the biological
relevance to humans of increases in common animal tumors, such
considerations should be weighed on their own merits and clearly
distinguished from statistical concerns.
When historical control data are used, the discussion should
address several issues that affect comparability of historical and
concurrent control data, such as genetic drift in the laboratory
strains, differences in pathology examination at different times and in
different laboratories (e.g., in criteria for evaluating lesions;
variations in the techniques for the preparation or reading of tissue
samples among laboratories), and comparability of animals from
different suppliers. The most relevant historical data come from the
same laboratory and the same supplier and are gathered within 2 or 3
years one way or the other of the study under review; other data should
be used only with extreme caution.
2.2.2.1.4. Assessment of Evidence of Carcinogenicity From Long-term
Animal Studies
In general, observation of tumors under different circumstances
lends support to the significance of the findings for animal
carcinogenicity. Significance is generally increased by the observation
of more of the factors listed below. For a factor such as malignancy,
the severity of the observed pathology can also affect the
significance. The following observations add significance to the tumor
findings:
Uncommon tumor types;
Tumors at multiple sites;
Tumors by more than one route of administration;
Tumors in multiple species, strains, or both sexes;
Progression of lesions from preneoplastic to benign to
malignant;
Reduced latency of neoplastic lesions;
Metastases;
Unusual magnitude of tumor response;
Proportion of malignant tumors; and
Dose-related increases.
In these cancer guidelines, tumors observed in animals are
generally assumed to indicate that an agent may produce tumors in
humans. Mode of action may help inform this assumption on a chemical-
specific basis. Moreover, the absence of tumors in well-conducted,
long-term animal studies in at least two species provides reasonable
assurance that an agent may not be a carcinogenic concern for humans.
2.2.2.1.5. Site Concordance
Site concordance of tumor effects between animals and humans should
be considered in each case. Thus far, there is evidence that growth
control mechanisms at the level of the cell are homologous among
mammals, but there is no evidence that these mechanisms are site
concordant. Moreover, agents observed to produce tumors in both humans
and animals have produced tumors either at the same site (e.g., vinyl
chloride) or different sites (e.g., benzene)(NRC, 1994). Hence, site
concordance is not always assumed between animals and humans. On the
other hand, certain modes of action with consequences for particular
tissue sites (e.g., disruption of thyroid function) may lead to an
anticipation of site concordance.
2.2.2.2. Perinatal Carcinogenicity Studies
The objective of perinatal carcinogenesis studies is to determine
[[Page 17784]]
the carcinogenic potential and dose-response relationships of the test
agent in the developing organism. Some investigators have hypothesized
that the age of initial exposure to a chemical carcinogen may influence
the carcinogenic response (Vesselinovitch et al., 1979; Rice, 1979;
McConnell, 1992). Current standardized long-term carcinogenesis
bioassays generally begin dosing animals at 6-8 weeks of age and
continue dosing for the lifespan of the animal (18-24 months). This
protocol has been modified in some cases to investigate the potential
of the test agent to induce transplacental carcinogenesis or to
investigate the potential differences following perinatal and adult
exposures, but currently there is not a standardized protocol for
testing agents for carcinogenic effects following prenatal or early
postnatal exposure.
Several cancer bioassay studies have compared adult and perinatal
exposures (see McConnell, 1992; U.S. EPA, 1996b). A review of these
studies reveals that perinatal exposure rarely identifies carcinogens
that are not found in standard animal bioassays. Exposure that is
perinatal can increase the incidence of a given type of tumor. The
increase may reflect an increased length of exposure and a higher dose
for the developing organism relative to the adult or an increase in
susceptibility in some cases. Additionally, exposure that is perinatal
through adulthood sometimes reduces the latency period for tumors to
develop in the growing organism (U.S. EPA, 1996b). EPA evaluates the
usefulness of perinatal studies on an agent-by-agent basis (e.g., U.S.
EPA, 1997a, b).
Perinatal study data analysis generally follows the principles
discussed above for evaluating other long-term carcinogenicity studies.
When differences in responses between perinatal animals and adult
animals suggest an increased susceptibility of perinatal or postnatal
animals, such as the ones below, a separate evaluation of the response
should be prepared:
A difference in dose-response relationship,
The presence of different tumor types,
An earlier onset of tumors, or
An increase in the incidence of tumors.
2.2.2.3. Other Studies
Intermediate-term and acute dosing studies often use protocols that
screen for carcinogenic or preneoplastic effects, sometimes in a single
tissue. Some protocols involve the development of various proliferative
lesions, such as foci of alteration in the liver (Goldsworthy et al.,
1986). Others use tumor endpoints, such as the induction of lung
adenomas in the sensitive strain A mouse (Maronpot et al., 1986) or
tumor induction in initiation-promotion studies using various organs
such as the bladder, intestine, liver, lung, mammary gland, and thyroid
(Ito et al., 1992). In these tests, the selected tissue rather than the
whole animal is, in a sense, the test system. Important information
concerning the steps in the carcinogenic process and mode of action can
be obtained from ``start/stop'' experiments. In these protocols, an
agent is given for a period of time to induce particular lesions or
effects and then stopped in order to evaluate the progression or
reversibility of processes (Todd, 1986; Marsman and Popp, 1994).
Assays in genetically engineered rodents may provide insight into
the chemical and gene interactions involved in carcinogenesis (Tennant
et al., 1995). These mechanistically based approaches involve activated
oncogenes that are introduced (transgenic) or tumor suppressor genes
that are deleted (knocked out). If appropriate genes are selected, not
only may these systems provide information on mechanisms, but the
rodents typically show tumor development earlier than in the standard
bioassay. Transgenic mutagenesis assays also represent a mechanistic
approach for assessing the mutagenic properties of agents as well as
developing quantitative linkages between exposure, internal dose, and
mutation related to tumor induction (Morrison and Ashby, 1994; Sisk et
al., 1994; Hayward et al., 1995).
The support that these studies give to a determination of
carcinogenicity rests on their contribution to the consistency of other
evidence about an agent. For instance, benzoyl peroxide has promoter
activity on the skin, but the overall evidence may be less supportive
(Kraus et al., 1995). These studies also may contribute information
about mode of action. It is important to recognize the limitations of
these experimental protocols, such as short duration, limited
histology, lack of complete development of tumors, or experimental
manipulation of the carcinogenic process, that may limit their
contribution to the overall assessment. Generally, their results are
appropriate as aids in the interpretation of other toxicological
evidence (e.g., rodent chronic bioassays), especially regarding
potential modes of action. On the basis of currently available
information, it is unlikely that any of these assays, which are
conducted for 6 months with 15 animals per group, will replace all
chronic bioassays for hazard identification (Spalding et al., 2000;
Gulezian et al., 2000; ILSI, 2001).
2.2.3. Structural Analogue Data
For some chemical classes, there is significant available
information, largely from rodent bioassays, on the carcinogenicity of
analogues. Analogue effects are instructive in investigating
carcinogenic potential of an agent as well as in identifying potential
target organs, exposures associated with effects, and potential
functional class effects or modes of action. All appropriate studies
should be included and analyzed, whether indicative of a positive
effect or not. Evaluation includes tests in various animal species,
strains, and sexes; with different routes of administration; and at
various doses, as data are available. Confidence in conclusions is a
function of how similar the analogues are to the agent under review in
structure, metabolism, and biological activity. It is important to
consider this confidence to ensure a balanced position.
2.3. Analysis of Other Key Data
The physical, chemical, and structural properties of an agent, as
well as data on endpoints that are thought to be critical elements of
the carcinogenic process, provide valuable insights into the likelihood
of human cancer risk. The following sections provide guidance for
analyses of these data.
2.3.1. Physicochemical Properties
Physicochemical properties affect an agent's absorption, tissue
distribution (bioavailability), biotransformation, and degradation in
the body and are important determinants of hazard potential (and dose-
response analysis). Properties that should be analyzed include, but are
not limited to, molecular weight, size, and shape; valence state;
physical state (gas, liquid, solid); water or lipid solubility, which
can influence retention and tissue distribution; and potential for
chemical degradation or stabilization in the body.
An agent's potential for chemical reaction with cellular
components, particularly with DNA and proteins, is also important. The
agent's molecular size and shape, electrophilicity, and charge
distribution are considered in order to decide whether they would
facilitate such reactions.
2.3.2. Structure-Activity Relationships (SARs)
SAR analyses and models can be used to predict molecular
properties, surrogate biological endpoints, and carcinogenicity (see,
e.g., Richard, 1998a, b; Richard and Williams, 2002;
[[Page 17785]]
Contrera et al., 2003). Overall, these analyses provide valuable
initial information on agents, they may strengthen or weaken concern,
and they are part of the weight of evidence.
Currently, SAR analysis is most useful for chemicals and
metabolites that are believed to initiate carcinogenesis through
covalent interaction with DNA (i.e., DNA-reactive, mutagenic,
electrophilic, or proelectrophilic chemicals) (Ashby and Tennant,
1991). For organic chemicals, the predictive capability of SAR analysis
combined with other toxicity information has been demonstrated (Ashby
and Tennant, 1994). The following parameters are useful in comparing an
agent to its structural analogues and congeners that produce tumors and
affect related biological processes such as receptor binding and
activation, mutagenicity, and general toxicity (Woo and Arcos, 1989):
Nature and reactivity of the electrophilic moiety or
moieties present;
Potential to form electrophilic reactive intermediate(s)
through chemical, photochemical, or metabolic activation;
Contribution of the carrier molecule to which the
electrophilic moiety(ies) is attached;
Physicochemical properties (e.g., physical state,
solubility, octanol/water partition coefficient, half-life in aqueous
solution);
Structural and substructural features (e.g., electronic,
stearic, molecular geometric);
Metabolic pattern (e.g., metabolic pathways and activation
and detoxification ratio); and
Possible exposure route(s) of the agent.
Suitable SAR analysis of non-DNA-reactive chemicals and of DNA-
reactive chemicals that do not appear to bind covalently to DNA should
be based on knowledge or postulation of the probable mode(s) of action
of closely related carcinogenic structural analogues (e.g., receptor
mediated, cytotoxicity related). Examination of the physicochemical and
biochemical properties of the agent may then provide the rest of the
information needed in order to make an assessment of the likelihood of
the agent's activity by that mode of action.
2.3.3. Comparative Metabolism and Toxicokinetics
Studies of the absorption, distribution, biotransformation, and
excretion of agents permit comparisons among species to assist in
determining the implications of animal responses for human hazard
assessment, supporting identification of active metabolites,
identifying changes in distribution and metabolic pathway or pathways
over a dose range, and making comparisons among different routes of
exposure.
If extensive data are available (e.g., blood/tissue partition
coefficients and pertinent physiological parameters of the species of
interest), physiologically based toxicokinetic models can be
constructed to assist in a determination of tissue dosimetry, species-
to-species extrapolation of dose, and route-to-route extrapolation
(Conolly and Andersen, 1991; see Section 3.1.2). If sufficient data are
not available, it may be assumed as a default that toxicokinetic and
metabolic processes are qualitatively comparable among species.
Discussion of appropriate procedures for quantitative, interspecies
comparisons appears in Chapter 3.
The qualitative question of whether an agent is absorbed by a
particular route of exposure is important for weight of evidence
classification, discussed in Section 2.5. Decisions about whether route
of exposure is a limiting factor on expression of any hazard, e.g.,
absorption does not occur by a specified route, are generally based on
studies in which effects of the agent or its structural analogues have
been observed by different routes, on physical-chemical properties, or
on toxicokinetics studies.
Adequate metabolism and toxicokinetic data can be applied toward
the following, as data permit. Confidence in conclusions is enhanced
when in vivo data are available.
Identifying metabolites and reactive intermediates of
metabolism and determining whether one or more of these intermediates
is likely to be responsible for the observed effects. Information on
the reactive intermediates focuses on SAR analysis, analysis of
potential modes of action, and estimation of internal dose in dose-
response assessment (D'Souza et al., 1987; Krewski et al., 1987).
Identifying and comparing the relative activities of
metabolic pathways in animals and in humans, and at different ages.
This analysis can provide insights for extrapolating results of animal
studies to humans.
Describing anticipated distribution within the body and
possibly identifying target organs. Use of water solubility, molecular
weight, and structure analysis can support qualitative inferences about
anticipated distribution and excretion. In addition, describing whether
the agent or metabolite of concern will be excreted rapidly or slowly
or whether it will be stored in a particular tissue or tissues to be
mobilized later can identify issues in comparing species and
formulating dose-response assessment approaches.
Identifying changes in toxicokinetics and metabolic
pathways with increases in dose. These changes may result in important
differences between high and low dose levels in disposition of the
agent or generation of its active forms. These studies play an
important role in providing a rationale for dose selection in
carcinogenicity studies.
Identifying and comparing metabolic process differences by
age, sex, or other characteristic so that susceptible subpopulations
can be recognized. For example, metabolic capacity with respect to P450
enzymes in newborn children is extremely limited compared to that in
adults, so that a carcinogenic metabolite formed through P450 activity
will have limited effect in the young, whereas a carcinogenic agent
deactivated through P450 activity will result in increased
susceptibility of this lifestage (Cresteil, 1998). A variety of changes
in toxicokinetics and physiology occur from the fetal stage to post-
weaning to young child. Any of these changes may make a difference for
risk (Renwick, 1998).
Determining bioavailability via different routes of
exposure by analyzing uptake processes under various exposure
conditions. This analysis supports identification of hazards for
untested routes. In addition, use of physicochemical data (e.g.,
octanol-water partition coefficient information) can support an
inference about the likelihood of dermal absorption (Flynn, 1990).
Attempts should be made in all of these areas to clarify and
describe as much as possible the variability to be expected because of
differences in species, sex, age, and route of exposure. The analysis
takes into account the presence of subpopulations of individuals who
are particularly vulnerable to the effects of an agent because of
toxicokinetic or metabolic differences (genetically or environmentally
determined) (Bois et al., 1995) and is a special emphasis for
assessment of risks to children.
2.3.4. Toxicological and Clinical Findings
Toxicological findings in experimental animals and clinical
observations in humans are important resources for the cancer hazard
assessment. Such findings provide information on physiological effects
and effects on enzymes, hormones, and other important macromolecules as
well
[[Page 17786]]
as on target organs for toxicity. For example, given that the cancer
process represents defects in processes such as terminal
differentiation, growth control, and cell death, developmental studies
of agents may provide an understanding of the activity of an agent that
carries over to cancer assessment. Toxicity studies in animals by
different routes of administration support comparison of absorption and
metabolism by those routes. Data on human variability in standard
clinical tests may also provide insight into the range of human
susceptibility and the common mechanisms of agents that affect the
tested parameters.
2.3.5. Events Relevant to Mode of Carcinogenic Action
Knowledge of the biochemical and biological changes that precede
tumor development (which include, but are not limited to, mutagenesis,
increased cell proliferation, inhibition of programmed cell death, and
receptor activation) may provide important insight for determining
whether a cancer hazard exists and may help inform appropriate
consideration of the dose-response relationship below the range of
observable tumor response. Because cancer can result from a series of
genetic alterations in the genes that control cell growth, division,
and differentiation (Vogelstein et al., 1988; Hanahan and Weinberg,
2000; Kinzler and Vogelstein, 2002), the ability of an agent to affect
genotype (and hence gene products) or gene expression is of obvious
importance in evaluating its influence on the carcinogenic process.
Initial and key questions to examine are: Does the agent (or its
metabolite) interact directly with DNA, leading to mutations that bring
about changes in gene products or gene expression? Does the agent bring
about effects on gene expression via other nondirect DNA interaction
processes?
Furthermore, carcinogenesis involves a complex series and interplay
of events that alter the signals a cell receives from its extracellular
environment, thereby promoting uncontrolled growth. Many, but not all,
mutagens are carcinogens, and some, but not all, agents that induce
cell proliferation lead to tumor development. Thus, understanding the
range of key steps in the carcinogenic process upon which an agent
might act is essential for evaluating its mode of action. Determination
of carcinogens that are operating by a mutagenic mode of action, for
example, entails evaluation of in vivo or in vitro short-term testing
results for genetic endpoints, metabolic profiles, physicochemical
properties, and structure-activity relationship (SAR) analyses in a
weight-of-evidence approach (Dearfield et al., 1991; U.S. EPA, 1986b;
Waters et al., 1999). Key data for a mutagenic mode of action may be
evidence that the carcinogen or a metabolite is DNA-reactive and/or has
the ability to bind to DNA. Also, mutagenic carcinogens usually produce
positive effects in multiple test systems for different genetic
endpoints, particularly gene mutations and structural chromosome
aberrations, and in tests performed in vivo which generally are
supported by positive tests in vitro. Additionally, carcinogens may be
identified as operating via a mutagenic mode of action if they have
similar properties and SAR to mutagenic carcinogens. Endpoints that
provide insight into an agent's ability to alter gene products and gene
expression, together with other features of an agent's potential mode
of carcinogenic action, are discussed below.
2.3.5.1. Direct DNA-Reactive Effects
It is well known that many carcinogens are electrophiles that
interact with DNA, resulting in DNA adducts and breakage (referred to
in these cancer guidelines as direct DNA effects). Usually during the
process of DNA replication, these DNA lesions can be converted into and
fixed as mutations and chromosomal alterations that then may initiate
and otherwise contribute to the carcinogenic process (Shelby and
Zeiger, 1990; Tinwell and Ashby, 1991; IARC, 1999). Thus, studies of
mutations and other genetic lesions continue to inform the assessment
of potential human cancer hazard and in the understanding of an agent's
mode of carcinogenic action.
EPA has published testing guidelines for detecting the ability of
an agent to damage DNA and produce mutations and chromosomal
alterations (as discussed in Dearfield et al., 1991). Briefly, standard
tests for gene mutations in bacteria and mammalian cells in vitro and
in vivo and for structural chromosomal aberrations in vitro and in vivo
are important examples of relevant methods. New molecular approaches,
such as mouse mutations and cancer transgenic models, are providing a
means to examine mutation at tissue sites where the tumor response is
observed (Heddle and Swiger, 1996; Tennant et al., 1999). Additionally,
continued improvements in fluorescent-based chromosome staining methods
(fluorescent in situ hybridization [FISH]) will allow the detection of
specific chromosomal abnormalities in relevant target tissues (Tucker
and Preston, 1998).
Endpoints indicative of DNA damage but not measures of mutation per
se, such as DNA adducts or strand breakage, may be detected in relevant
target tissues and thus contribute to evaluating an agent's mutagenic
potential. Evidence of chemical-specific DNA adducts (e.g., reactions
at oxygen sites in DNA bases or with ring nitrogens of guanine and
adenine) provides information on a mutagen's ability to directly
interact with DNA (La and Swenberg, 1996). Some planar molecules (e.g.,
9-aminoacridine) intercalate between base pairs of DNA, which results
in a physical distortion in DNA that may lead to mutations when DNA
replicates. As discussed below, some carcinogens do not interact
directly with DNA, but they can produce increases in endogenous levels
of DNA adducts (e.g., 8-hydroxyguanine) by indirect mechanisms.
2.3.5.2. Indirect DNA Effects or Other Effects on Genes/Gene Expression
Although some carcinogens may result in an elevation of mutations
or cytogenetic anomalies, as detected in standard assays, they may do
so by indirect mechanisms. These effects may be brought about by
chemical-cell interactions rather than by the chemical (or its
metabolite) directly interacting with DNA. An increase in mutations
might be due to cytotoxic exposures causing regenerative proliferation
or to mitogenic influences (Cohen and Ellwein, 1990). Increased cell
division may elevate mutation by clonal expansion of initiated cells or
by increasing the number of genetic errors by rapid cell division and
reduced time for DNA repair. Some agents might result in an elevation
of mutations by interfering with the enzymes involved in DNA repair and
recombination (Barrett and Lee, 1992). Damage to certain critical DNA
repair genes or other genes (e.g., the p53 gene) may result in genomic
instability, which predisposes cells to further genetic alterations and
increases the probability of neoplastic progression (Harris and
Hollstein, 1993; Levine et al., 1994; Rouse and Jackson, 2002).
Likewise, DNA repair processes may be saturated at certain doses of a
chemical, leading to an elevation of genetic alterations.
The initiation of programmed cell death (apoptosis) can potentially
be blocked by an agent, thereby permitting replication of cells
carrying genetic errors that would normally be removed from the
proliferative pool. At certain doses an agent may also generate
reactive oxygen species that produce oxidative damage to DNA and other
[[Page 17787]]
macromolecules (Chang et al. 1988; Kehrer, 1993; Clayson et al., 1994).
The role of cellular alterations that are attributable to oxidative
damage in tumorigenesis (e.g., 8-hydroxyguanine) is currently unclear.
Several carcinogens have been shown to induce aneuploidy (the loss
or gain of chromosomes) (Barrett, 1992; Gibson et al., 1995).
Aneuploidy can result in the loss of heterozygosity or genomic
instability (Cavenee et al., 1986; Fearon and Vogelstein, 1990). Agents
that cause aneuploidy typically interfere with the normal process of
chromosome segregation by interacting with non-DNA targets such as the
proteins needed for chromosome segregation and chromosome movement.
Whether this chromosome imbalance is the cause or the effect of
tumorigenesis is not clear. Thus, it is important to understand if the
agent induces aneuploidy as a key early event in the carcinogenic
process.
It is possible for an agent to alter gene expression by
transcriptional, translational, or post-translational modifications.
For example, perturbation of DNA methylation patterns may cause effects
that contribute to carcinogenesis (Jones, 1986; Holliday, 1987; Goodman
and Counts, 1993; Chuang et al., 1996; Baylin and Bestor, 2002).
Overexpression of genes by DNA amplification has been observed in
certain tumors (Vainio et al., 1992). Mechanisms of altering gene
expression may involve cellular reprogramming through hormonal or
receptor-mediated mechanisms (Barrett, 1992; Ashby et al., 1994).
Both cell proliferation and programmed cell death can be part of
the maintenance of homeostasis in many normal tissues, and alterations
in the level or rate of either can be important elements of the
carcinogenic process. The balance between the two can directly affect
the survival and growth of initiated cells as well as preneoplastic and
tumor cell populations (i.e., increase in cell proliferation or
decrease in cell death) (Moolgavkar, 1986; Cohen and Ellwein, 1990,
1991; Cohen et al., 1991; Bellamy et al., 1995). Thus, measurements of
these events can contribute to the weight of the evidence for cancer
hazard prediction and to mode of action understanding. In studies of
proliferative effects, distinctions should be made between mitogenesis
and regenerative proliferation (Cohen and Ellwein, 1990, 1991; Cohen et
al., 1991).
In applying information from studies on cell proliferation and
apoptosis to risk assessment, it is important to identify the tissues
and target cells involved, to measure effects in both normal and
neoplastic tissue, to distinguish between apoptosis and necrosis, and
to determine the dose that affects these processes. Gap-junctional
intercellular communication is believed to play a role in tissue and
organ development and in the maintenance of a normal cellular phenotype
within tissues. A growing body of evidence suggests that chemical
interference with gap-junctional intercellular communication is a
contributing factor in tumor development (Swierenga and Yamasaki, 1992;
Yamasaki, 1995).
2.3.5.3. Precursor Events and Biomarker Information
Most testing schemes for mutagenicity and other short-term assays
were designed for hazard identification purposes; thus, these assays
are generally conducted using acute exposures. For data on ``precursor
steps'' to be useful in informing the dose-response curve for tumor
induction below the level of observation, it is often useful for data
to come from in vivo studies and from studies where exposure is
repeated or given over an extended period of time. Although consistency
of results across different assays and animal models provides a
stronger basis for drawing conclusions, it is desirable to have data on
the precursor event in the same target organ, sex, animal strain, and
species as the tumor data. In evaluating an agent's mode of action, it
is usually not sufficient to determine that some event commences upon
dosing. It is important to understand whether it is a necessary event
that plays a key role in the process that leads to tumor development
versus an effect of the cancer process itself or simply an associated
event.
Various endpoints can serve as biological markers of effects in
biological systems or samples. These may help identify doses at which
elements of the carcinogenic process are operating; aid in interspecies
extrapolations when data are available from both experimental animal
and human cells; and under certain circumstances, provide insights into
the possible shape of the dose-response curve below levels where tumor
incidences are observed (e.g., Choy, 1993).
Genetic and other findings (such as changes in proto-oncogenes and
tumor suppressor genes in preneoplastic and neoplastic tissue or,
possibly, measures of endocrine disruption) can indicate the potential
for disease and, as such, serve as biomarkers of effect. They, too, can
be used in different ways.
The spectrum of genetic changes in proliferative lesions
and tumors following chemical administration to experimental animals
can be determined and compared with that in spontaneous tumors in
control animals, in animals exposed to other agents of varying
structural and functional activities, and in persons exposed to the
agent under study.
Biomarkers of effect and/or precursors may help to
identify subpopulations of individuals who may be at an elevated risk
for a certain cancer or exposure to a certain agent, e.g., cytochrome
P450 2D6/debrisoquine sensitivity for lung cancer (Caporaso et al.,
1989) or inherited colon cancer syndromes (Kinzler et al., 1991;
Peltom[auml]ki et al., 1993).
As with biomarkers of exposure, it may be justified in
some cases to use biomarkers of effect and/or precursors for dose-
response assessment or to provide insight into the potential shape of
the dose-response curve at doses below those at which tumors are
induced experimentally.
In applying biomarker data to cancer assessment an assessment
should consider:
Analytical methodology,
Routes of exposure,
Exposure to mixtures,
Time after exposure,
Sensitivity and specificity of biomarkers, and
Dose-response relationships.
2.3.5.4. Judging Data
Criteria that are generally applicable for judging the adequacy of
mechanistically based data include:
Mechanistic relevance of the data to carcinogenicity,
Number of studies of each endpoint,
Consistency of results in different test systems and
different species,
Similar dose-response relationships for tumor and mode of
action-related effects,
Conduct of the tests in accordance with generally accepted
protocols, and
Degree of consensus and general acceptance among
scientists regarding interpretation of the significance and specificity
of the tests.
Although important information can be gained from in vitro test
systems, a higher level of confidence is generally given to data that
are derived from in vivo systems, particularly those results that show
a site concordance with the tumor data.
It is important to remember that when judging and considering the
use of any data, the basic standard of quality, as defined by the EPA
Information Quality Guidelines, should be satisfied.
[[Page 17788]]
2.4. Mode of Action--General Considerations and Framework for Analysis
2.4.1. General Considerations
The interaction between the biology of the organism and the
chemical properties of the agent determine whether there is an adverse
effect. Thus, mode of action analysis is based on physical, chemical,
and biological information that helps to explain key events in an
agent's influence on development of tumors. The entire range of
information developed in the assessment is reviewed to arrive at a
reasoned judgment. An agent may work by more than one mode of action,
both at different sites and at the same tumor site. Thus the mode of
action and human relevance cannot necessarily be generalized to other
toxic endpoints or tissues or cell types without additional analyses
(IPCS, 1999; Meek et al., 2003). At least some information bearing on
mode of action (e.g., SAR, screening tests for mutagenicity) is present
for most agents undergoing assessment of carcinogenicity, even though
certainty about exact molecular mechanisms may be rare.
Information for mode of action analysis generally includes tumor
data in humans and animals and among structural analogues, as well as
the other key data. The more complete the data package and the generic
knowledge about a given mode of action, the more confidence one has and
the more one can rely on assessment of available data rather than
reverting to default options to address the absence of information on
mode of action. Reasoned judgments are generally based on a data-rich
source of chemical, chemical class, and tumor type-specific
information. Many times there will be conflicting data and gaps in the
information base; it is important to carefully evaluate these
uncertainties before reaching any conclusion.
In making decisions about potential modes of action and the
relevance of animal tumor findings to humans (Ashby et al., 1990; Ashby
and Tennant, 1991; Tennant, 1993; IPCS 1999; Sonich-Mullin et al.,
2001; Meek et al., 2003), very often the results of chronic animal
studies may give important clues. Some of the important factors to
review include:
Tumor types, for example, those responsive to endocrine
influence or those produced by DNA-reactive carcinogens;
Number of studies and of tumor sites, sexes, and species
affected or unaffected in those studies and if the data present a
coherent story;
Similarity of metabolic activation and detoxification for
a specific chemical between humans and tested species;
Influence of route of exposure on the spectrum of tumors
and whether they occur at point of exposure or systemic sites;
Effect of high dose exposures on the target organ or
systemic toxicity that may not reflect typical physiological
conditions, for example, urinary chemical changes associated with stone
formation, effects on immune surveillance;
Presence of proliferative lesions, for example, hepatic
foci, or hyperplasia;
Effect of dose and time on the progression of lesions from
preneoplastic to benign tumors, then to malignant;
Ratio of malignant to benign tumors as a function of dose
and time;
Time of appearance of tumors after commencing exposure;
Development of tumors that invade locally or systemically,
or lead to death;
Tumors at organ sites with high or low background
historical incidence in laboratory animals;
Biomarkers in tumor cells, both induced and spontaneous,
for example, DNA or protein adducts, mutation spectra, chromosome
changes, oncogene activation; and/or
Shape of the dose-response curve in the range of tumor
observation, for example, linear versus nonlinear.
Some of the myriad ways in which information from chronic animal
studies influences mode of action judgments include, but are not
limited to, the following:
Multisite and multispecies tumor effects that are often
associated with mutagenic agents;
Tumors restricted to one sex or species suggesting an
influence restricted to gender, strain, or species;
Late onset of tumors that are primarily benign, are at
sites with a high historical background incidence, or show reversal of
lesions on cessation of exposure suggesting a growth-promoting mode of
action;
The possibility that an agent acting differently in
different tissues; or
The possibility that has more than one mode of action in a
single tissue.
Simple knowledge of sites of tumor increase in rodent studies can
give preliminary clues as to mode of action. Experience at the National
Toxicology Program (NTP) indicates that substances that are DNA
reactive and that produce gene mutations may be unique in producing
tumors in certain anatomical sites, whereas tumors at other sites may
arise from both mutagenic or nonmutagenic influences (Ashby and
Tennant, 1991; Huff et al., 1991).
The types of data and their influence on judgments regarding mode
of action are expected to evolve, both as science advances and as the
risk assessment community gains more experience with these analyses.
This section contains a framework for evaluating hypothesized mode(s)
of action. This framework has similarities to and differences with the
concepts presented in other MOA frameworks (e.g., IPCS, 1999; Sonich-
Mullin et al., 2001; Meek et al., 2003). Differences are often due to
the context of the use for the framework. For example, the Meek et al.
(2003) presents a stand-alone document for addressing mode of action
issues; thus, it recommends that conclusions concerning MOA be rendered
separately. In these cancer guidelines, however, they are incorporated
into the context of all of the data regarding weight of the evidence
for carcinogenicity.
2.4.2. Evaluating an Hypothesized Mode of Action
2.4.2.1. Peer Review
In reaching conclusions, the question of ``general acceptance'' of
a mode of action should be tested as part of the independent peer
review that EPA obtains for its assessment and conclusions. In some
cases the mode of action may already have been established by
development of a large body of research information and
characterization of the phenomenon over time. In some cases there will
have been development of an Agency policy (e.g., mode of action
involving alpha-2u-globulin in the male rat [U.S. EPA, 1991b]) or a
series of previous assessments in which both the mode of action and its
applicability to particular cases has been explored. If so, the
assessment and its peer review can focus on the evidence that a
particular agent acts in this mode. The peer review should also
evaluate the strengths and weaknesses of competing modes of action.
In other cases, the mode of action may not have previously been the
subject of an Agency document. If so, the data to support both the mode
of action and the associated activity of the agent should undergo EPA
assessment and subsequent peer review.
2.4.2.2. Use of the Framework
The framework supports a full analysis of mode of action
information, but it can also be used as a screen to decide whether
sufficient information is available to evaluate or whether the data
[[Page 17789]]
gaps are too substantial to justify further analysis. Mode of action
conclusions are used to address the question of human relevance of
animal tumor responses, to address differences in anticipated response
among humans, such as between children and adults or men and women; and
as the basis of decisions about the anticipated shape of the dose-
response relationship. Guidance on the latter appears in Section 3.
This framework is intended to provide an analytical approach for
evaluating the mode of action. It is neither a checklist nor a list of
required criteria. As the type and amount of information will depend on
the mode of action postulated, scientific judgment is important to
determine if the weight of evidence is sufficient.
2.4.3. Framework for Evaluating Each Hypothesized Carcinogenic Mode of
Action
This framework is intended to be an analytic tool for judging
whether available data support a mode of carcinogenic action
hypothesized for an agent. It is based upon considerations for
causality in epidemiologic investigations originally articulated by
Hill (1965) but later modified by others and extended to experimental
studies. The original Hill criteria were applied to epidemiologic data,
whereas this framework is applied to a much wider assortment of
experimental data, so it retains the basic principles of Hill but is
much modified in content.
The modified Hill criteria can be useful for organizing thinking
about aspects of causation, and they are consistent with the scientific
method of developing hypotheses and testing those hypotheses
experimentally. During analysis by EPA, and as guidance for peer
review, a key question is whether the data to support a mode of action
meet the standards generally applied in experimental biology regarding
inference of causation.
All pertinent studies are reviewed in analyzing a mode of action,
and an overall weighing of evidence is performed, laying out the
strengths, weaknesses, and uncertainties of the case as well as
potential alternative positions and rationales. Identifying data gaps
and research needs is also part of the assessment.
To evaluate whether an hypothesized mode of action is operative, an
analysis starts with an outline of the scientific findings regarding
the hypothesized key events leading to cancer, and then weighing
information to determine whether there is a causal relationship between
these events and cancer formation, i.e., that the effects are critical
for induction of tumors. It is not generally expected that the complete
sequence will be known at the molecular level. Instead, empirical
observations made at different levels of biological organization--
biochemical, cellular, physiological, tissue, organ, and system--are
analyzed.
Several important points should be considered when working with the
framework:
The topics listed for analysis should not be regarded as a
checklist of necessary ``proofs.'' The judgment of whether an
hypothesized mode of action is supported by available data takes
account of the analysis as a whole.
The framework provides a structure for organizing the
facts upon which conclusions as to mode of action rest. The purpose of
using the framework is to make analysis transparent and to allow the
reader to understand the facts and reasoning behind a conclusion.
The framework does not dictate an answer. The weight of
evidence that is sufficient to support a decision about a mode of
action may be less or more, depending on the purpose of the analysis,
for example, screening, research needs identification, or full risk
assessment. To make the reasoning transparent, the purpose of the
analysis should be made apparent to the reader.
Toxicokinetic studies may contribute to mode of action
analysis by contributing to identifying the active form(s) of an agent
that is central to the mode of action. Apart from contributing in this
way, toxicokinetics studies may reveal effects of saturation of
metabolic processes. These may not be considered key events in a mode
of action, but they are given separate consideration in assessing dose
metrics and potential nonlinearity of the dose-response relationship.
Generally, ``sufficient'' support is a matter of
scientific judgment in the context of the requirements of the
decisionmaker or in the context of science policy guidance regarding a
certain mode of action.
Even when an hypothesized mode of action is supported for
a described response in a specific tissue, it may not explain other
tumor responses observed, which should get separate consideration in
hazard and dose-response assessment.
For each tumor site being evaluated, the mode of action analysis
should begin with a description of the relevant data and key events
that may be associated with an hypothesized mode of action and its
sequence of key events (see Section 2.4.3.1). This can be followed by a
discussion of various aspects of the experimental support for
hypothesized mode(s) of action in animals and humans (see Section
2.4.3.2). The possibility of other modes of action also should be
considered and discussed (see Section 2.4.3.3); if there is evidence
for more than one mode of action, each should receive a separate
analysis. Conclusions about each hypothesized mode of action should
address whether the mode of action is supported in animals and is
relevant to humans and which populations or lifestages can be
particularly susceptible (see Section 2.4.3.4). In a risk assessment
document, the analysis of an hypothesized mode of action can be
presented before or with the characterization of an agent's potential
hazard to humans.
2.4.3.1. Description of the Hypothesized Mode of Action
Summary description of the hypothesized mode of action. For each
tumor site, the mode of action analysis begins with a description of
the hypothesized mode of action and its sequence of key events. If
there is evidence for more than one mode of action, each receives a
separate analysis.
Identification of key events. In order to judge how well data
support involvement of a key event in carcinogenic processes, the
experimental definition of the event or events should be clear and
reproducible. To support an association, experiments should define and
measure an event consistently.
Can a list of events be identified that are key to the
carcinogenic process?
Are the events well defined?
Pertinent observations may include, but are not limited to,
receptor-ligand changes, cytotoxicity, cell cycle effects, increased
cell growth, organ weight differences, histological changes, hormone or
other protein perturbations, or DNA and chromosome effects.
2.4.3.2. Discussion of the Experimental Support for the Hypothesized
Mode of Action
The experimental support for the hypothesized mode of action should
be discussed from several viewpoints patterned after the Hill criteria
(see Section 2.2.1.7). For illustration, the explanation of each topic
includes typical questions to be addressed to the available empirical
data and experimental observations anticipated to be pertinent. The
latter will vary from case to case. For a particular mode of action,
certain observations may be established as essential in practice or
policy, for example, measures of thyroid hormone levels in supporting
thyroid
[[Page 17790]]
hormone elevation as a key event in carcinogenesis.
Strength, consistency, specificity of association. A statistically
significant association between events and a tumor response observed in
well-conducted studies is generally supportive of causation. Consistent
observations in a number of such studies with differing experimental
designs increase that support, because different designs may reduce
unknown biases. Studies showing ``recovery,'' i.e., absence or
reduction of carcinogenicity when the event is blocked or diminished,
are particularly useful tests of the association. Specificity of the
association, without evidence of other modes of action, strengthens a
causal conclusion. A lack of strength, consistency, and specificity of
association weakens the causal conclusions for a particular mode of
action.
What is the level of statistical and biological
significance for each event and for cancer?
Do independent studies and different experimental
hypothesis-testing approaches produce the same associations?
Does the agent produce effects other than those
hypothesized?
Is the key event associated with precursor lesions?
Pertinent observations include tumor response associated with
events (site of action logically relates to event[s]), precursor
lesions associated with events, initiation-promotion studies, and stop/
recovery studies.
Dose-response concordance. If a key event and tumor endpoints
increase with dose such that the key events forecast the appearance of
tumors at a later time or higher dose, a causal association can be
strengthened. Dose-response associations of the key event with other
precursor events can add further strength. Difficulty arises when an
event is not causal but accompanies the process generally. For example,
if tumors and the hypothesized precursor both increase with dose, the
two responses will be correlated regardless of whether a causal
relationship exists. This is similar to the issue of confounding in
epidemiologic studies. Dose-response studies coupled with mechanistic
studies can assist in clarifying these relationships.
What are the correlations among doses producing events and
cancer?
Pertinent observations include, but are not limited to, 2-year
bioassay observation of lesions correlated with observations of hormone
changes and the same lesions in shorter term studies or in interim
sacrifice.
Temporal relationship. If an event is shown to be causally linked
to tumorigenesis, it will precede tumor appearance. An event may also
be observed contemporaneously or after tumor appearance; these
observations may add to the strength of association but not to the
temporal association.
What is the ordering of events that underlie the
carcinogenic process?
Is this ordering consistent among independent studies?
Pertinent observations include studies of varying duration
observing the temporal sequence of events and development of tumors.
Biological plausibility and coherence. It is important that the
hypothesized mode of action and the events that are part of it be based
on contemporaneous understanding of the biology of cancer to be
accepted. If the body of information under scrutiny is consistent with
other examples (including structurally related agents) for which the
hypothesized mode of action is accepted, the case is strengthened.
Because some modes of action can be anticipated to evoke effects other
than cancer, the available toxicity database on noncancer effects, for
example, reproductive effects of certain hormonal disturbances, can
contribute to this evaluation.
Is the mode of action consistent with what is known about
carcinogenesis in general and for the case specifically?
Are carcinogenic effects and events consistent across
structural analogues?
Is the database on the agent internally consistent in
supporting the purported mode of action, including relevant noncancer
toxicities?
Pertinent observations include the scientific basis for considering
an hypothesized mode of action generally, given the contemporaneous
state of knowledge of carcinogenic processes; previous examples of data
sets showing the mode of action; data sets on analogues; and coherence
of data in this case from cancer and noncancer toxicity studies.
2.4.3.3. Consideration of the Possibility of Other Modes of Action
The possible involvement of more than one mode of action at the
tumor site should be considered. Pertinent observations that are not
consistent with the hypothesized mode of action can suggest the
possibility of other modes of action. Some pertinent observations can
be consistent with more than one mode of action. Furthermore, different
modes of action can operate in different dose ranges; for example, an
agent can act predominantly through cytotoxicity at high doses and
through mutagenicity at lower doses where cytotoxicity may not occur.
If there is evidence for more than one mode of action, each should
receive a separate analysis. There may be an uneven level of
experimental support for the different modes of action. Sometimes this
can reflect disproportionate resources spent on investigating one
particular mode of action and not the validity or relative importance
of the other possible modes of action. Ultimately, however, the
information on all of the modes of action should be integrated to
better understand how and when each mode acts, and which mode(s) may be
of interest for exposure levels relevant to human exposures of
interest.
2.4.3.4. Conclusions About the Hypothesized Mode of Action
Conclusions about the hypothesized mode of action should address
the issues listed below. For those agents for which the mode of action
is considered useful for the risk assessment, the weight of the
evidence concerning mode of action in animals as well as its relevance
for humans would be incorporated into the weight of evidence narrative
(Section 2.5).
(a) Is the hypothesized mode of action sufficiently supported in
the test animals? Associations observed between key events and tumors
may or may not support an inference of causation. The conclusion that
the agent causes one or more key events that results in tumors is
strengthened as more aspects of causation are satisfied and weakened as
fewer are satisfied. Consistent results in different experiments that
test the hypothesized mode of action build support for that mode of
action. Replicating results in a similar experiment does not generally
meaningfully strengthen the original evidence, and discordant results
generally weaken that support. Experimental challenge to the
hypothesized mode of action, where interrupting the sequence of key
events suppresses the tumor response or enhancement of key events
increases the tumor response, creates very strong support for the mode
of action.
(b) Is the hypothesized mode of action relevant to humans? If an
hypothesized mode of action is sufficiently supported in the test
animals, the sequence of key precursor events should be reviewed to
identify critical similarities and differences between the test animals
and humans. The question of concordance can be complicated by cross-
species differences in toxicokinetics or toxicodynamics. For example,
the active
[[Page 17791]]
agent can be formed through different metabolic pathways in animals and
humans. Any information suggesting quantitative differences between
animals and humans is flagged for consideration in the dose-response
assessment. This includes the potential for different internal doses of
the active agent or for differential occurrence of a key precursor
event.
``Relevance'' of a potential mode of action is considered in the
context of characterization of hazard, not level of risk. Anticipated
levels of human exposure are not used to determine whether the
hypothesized mode of action is relevant to humans. Exposure information
is integrated into the overall risk characterization.
The question of relevance considers all populations and lifestages.
It is possible that the conditions under which a mode of action
operates exist primarily in a particular population or lifestage, for
example, in those with a pre-existing hormonal imbalance. Other
populations or lifestages may not be analogous to the test animals, in
which case the question of relevance would be decided by inference.
Special attention should be paid to whether tumors can arise from
childhood exposure, considering various aspects of development during
these lifestages. Because the studies that support a mode of action are
typically conducted in mature animals, conclusions about relevance
during childhood generally rely on inference. There is currently no
standard Agency position regarding the issue of whether tumors arising
through the hypothesized mode of action are relevant during childhood;
understanding the mode of action implies that there are sufficient data
(on either the specific agent or the general mode of action) to form a
confident conclusion about relevance during childhood.
(c) Which populations or lifestages can be particularly susceptible
to the hypothesized mode of action? If an hypothesized mode of action
is judged relevant to humans, information about the key precursor
event(s) is reviewed to identify populations or lifestages that might
reasonably expected to be particularly susceptible to their occurrence.
Although agent-specific data would provide the strongest indication of
susceptibility, this review may also rely on general knowledge about
the precursor events and characteristics of individuals susceptible to
these events. Any information suggesting quantitative differences
between populations or lifestages should be flagged for consideration
in the dose-response assessment (see Section 3.5). This includes the
potential for a higher internal dose of the active agent or for an
increased occurrence of a key precursor event. Quantitative differences
may result in separate risk estimates for susceptible populations or
lifestages.
The possibility that childhood is a susceptible period for exposure
should be explicitly addressed. Generic understanding of the mode of
action can be used to gauge childhood susceptibility, and this
determination can be refined through analysis of agent-specific data.
2.4.4. Evolution With Experience
Several groups have proposed or incorporated mode of action into
their risk assessments (see, e.g., U.S. EPA, 1991b; Sonich-Mullin et
al., 2001; Meek et al., 2003). As the frameworks and mandates under
which these evaluations were produced differ, the specific procedures
described in and conclusions drawn may also differ. Nevertheless, the
number of case studies from all venues remains limited. More experience
with differing modes of action are expected to highlight and illustrate
the strengths and limitations of the general framework proposed in
these cancer guidelines. Moreover, additional toxicological techniques
may expand or change scientific judgments regarding which information
is useful for mode of action determinations. As warranted, additional
guidance may be proposed as experience is gained and/or as
toxicological knowledge advances.
2.5. Weight of Evidence Narrative
The weight of evidence narrative is a short summary (one to two
pages) that explains an agent's human carcinogenic potential and the
conditions that characterize its expression. It should be sufficiently
complete to be able to stand alone, highlighting the key issues and
decisions that were the basis for the evaluation of the agent's
potential hazard. It should be sufficiently clear and transparent to be
useful to risk managers and non-expert readers. It may be useful to
summarize all of the significant components and conclusions in the
first paragraph of the narrative and to explain complex issues in more
depth in the rest of the narrative.
The weight of the evidence should be presented as a narrative
laying out the complexity of information that is essential to
understanding the hazard and its dependence on the quality, quantity,
and type(s) of data available, as well as the circumstances of exposure
or the traits of an exposed population that may be required for
expression of cancer. For example, the narrative can clearly state to
what extent the determination was based on data from human exposure,
from animal experiments, from some combination of the two, or from
other data. Similarly, information on mode of action can specify to
what extent the data are from in vivo or in vitro exposures or based on
similarities to other chemicals. The extent to which an agent's mode of
action occurs only on reaching a minimum dose or a minimum duration
should also be presented. A hazard might also be expressed
disproportionately in individuals possessing a specific gene; such
characterizations may follow from a better understanding of the human
genome. Furthermore, route of exposure should be used to qualify a
hazard if, for example, an agent is not absorbed by some routes.
Similarly, a hazard can be attributable to exposures during a
susceptible lifestage on the basis of our understanding of human
development.
The weight of evidence-of-evidence narrative should highlight:
The quality and quantity of the data;
All key decisions and the basis for these major decisions;
and
Any data, analyses, or assumptions that are unusual for or
new to EPA.
To capture this complexity, a weight of evidence narrative
generally includes:
Conclusions about human carcinogenic potential (choice of
descriptor(s), described below),
A summary of the key evidence supporting these conclusions
(for each descriptor used), including information on the type(s) of
data (human and/or animal, in vivo and/or in vitro) used to support the
conclusion(s),
Available information on the epidemiologic or experimental
conditions that characterize expression of carcinogenicity (e.g., if
carcinogenicity is possible only by one exposure route or only above a
certain human exposure level),
A summary of potential modes of action and how they
reinforce the conclusions,
Indications of any susceptible populations or lifestages,
when available, and
A summary of the key default options invoked when the
available information is inconclusive.
To provide some measure of clarity and consistency in an otherwise
free-form narrative, the weight of evidence descriptors are included in
the first sentence of the narrative. Choosing a descriptor is a matter
of judgment and cannot be reduced to a formula. Each descriptor may be
applicable to a wide
[[Page 17792]]
variety of potential data sets and weights of evidence. These
descriptors and narratives are intended to permit sufficient
flexibility to accommodate new scientific understanding and new testing
methods as they are developed and accepted by the scientific community
and the public. Descriptors represent points along a continuum of
evidence; consequently, there are gradations and borderline cases that
are clarified by the full narrative. Descriptors, as well as an
introductory paragraph, are a short summary of the complete narrative
that preserves the complexity that is an essential part of the hazard
characterization. Users of these cancer guidelines and of the risk
assessments that result from the use of these cancer guidelines should
consider the entire range of information included in the narrative
rather than focusing simply on the descriptor.
In borderline cases, the narrative explains the case for choosing
one descriptor and discusses the arguments for considering but not
choosing another. For example, between ``suggestive'' and ``likely'' or
between ``suggestive'' and ``inadequate,'' the explanation clearly
communicates the information needed to consider appropriately the
agent's carcinogenic potential in subsequent decisions.
Multiple descriptors can be used for a single agent, for example,
when carcinogenesis is dose-or route-dependent. For example, if an
agent causes point-of-contact tumors by one exposure route but adequate
testing is negative by another route, then the agent could be described
as likely to be carcinogenic by the first route but not likely to be
carcinogenic by the second. Another example is when the mode of action
is sufficiently understood to conclude that a key event in tumor
development would not occur below a certain dose range. In this case,
the agent could be described as likely to be carcinogenic above a
certain dose range but not likely to be carcinogenic below that range.
Descriptors can be selected for an agent that has not been tested
in a cancer bioassay if sufficient other information, e.g.,
toxicokinetic and mode of action information, is available to make a
strong, convincing, and logical case through scientific inference. For
example, if an agent is one of a well-defined class of agents that are
understood to operate through a common mode of action and if that agent
has the same mode of action, then in the narrative the untested agent
would have the same descriptor as the class. Another example is when an
untested agent's effects are understood to be caused by a human
metabolite, in which case in the narrative the untested agent could
have the same descriptor as the metabolite. As new testing methods are
developed and used, assessments may increasingly be based on inferences
from toxicokinetic and mode of action information in the absence of
tumor studies in animals or humans.
When a well-studied agent produces tumors only at a point of
initial contact, the descriptor generally applies only to the exposure
route producing tumors unless the mode of action is relevant to other
routes. The rationale for this conclusion would be explained in the
narrative.
When tumors occur at a site other than the point of initial
contact, the descriptor generally applies to all exposure routes that
have not been adequately tested at sufficient doses. An exception
occurs when there is convincing information, e.g., toxicokinetic data
that absorption does not occur by another route.
When the response differs qualitatively as well as quantitatively
with dose, this information should be part of the characterization of
the hazard. In some cases reaching a certain dose range can be a
precondition for effects to occur, as when cancer is secondary to
another toxic effect that appears only above a certain dose. In other
cases exposure duration can be a precondition for hazard if effects
occur only after exposure is sustained for a certain duration. These
considerations differ from the issues of relative absorption or potency
at different dose levels because they may represent a discontinuity in
a dose-response function.
When multiple bioassays are inconclusive, mode of action data are
likely to hold the key to resolution of the more appropriate
descriptor. When bioassays are few, further bioassays to replicate a
study's results or to investigate the potential for effects in another
sex, strain, or species may be useful.
When there are few pertinent data, the descriptor makes a statement
about the database, for example, ``Inadequate Information to Assess
Carcinogenic Potential,'' or a database that provides ``Suggestive
Evidence of Carcinogenic Potential.'' With more information, the
descriptor expresses a conclusion about the agent's carcinogenic
potential to humans. If the conclusion is positive, the agent could be
described as ``Likely to Be Carcinogenic to Humans'' or, with strong
evidence, ``Carcinogenic to Humans.'' If the conclusion is negative,
the agent could be described as ``Not Likely to Be Carcinogenic to
Humans.''
Although the term ``likely'' can have a probabilistic connotation
in other contexts, its use as a weight of evidence descriptor does not
correspond to a quantifiable probability of whether the chemical is
carcinogenic. This is because the data that support cancer assessments
generally are not suitable for numerical calculations of the
probability that an agent is a carcinogen. Other health agencies have
expressed a comparable weight of evidence using terms such as
``Reasonably Anticipated to Be a Human Carcinogen'' (NTP) or ``Probably
Carcinogenic to Humans'' (International Agency for Research on Cancer).
The following descriptors can be used as an introduction to the
weight of evidence narrative. The examples presented in the discussion
of the descriptors are illustrative. The examples are neither a
checklist nor a limitation for the descriptor. The complete weight of
evidence narrative, rather than the descriptor alone, provides the
conclusions and the basis for them.
``Carcinogenic to Humans.'' This descriptor indicates strong
evidence of human carcinogenicity. It covers different combinations of
evidence.
This descriptor is appropriate when there is convincing
epidemiologic evidence of a causal association between human exposure
and cancer.
Exceptionally, this descriptor may be equally appropriate
with a lesser weight of epidemiologic evidence that is strengthened by
other lines of evidence. It can be used when all of the following
conditions are met: (a) There is strong evidence of an association
between human exposure and either cancer or the key precursor events of
the agent's mode of action but not enough for a causal association, and
(b) there is extensive evidence of carcinogenicity in animals, and (c)
the mode(s) of carcinogenic action and associated key precursor events
have been identified in animals, and (d) there is strong evidence that
the key precursor events that precede the cancer response in animals
are anticipated to occur in humans and progress to tumors, based on
available biological information. In this case, the narrative includes
a summary of both the experimental and epidemiologic information on
mode of action and also an indication of the relative weight that each
source of information carries, e.g., based on human information, based
on limited human and extensive animal experiments.
``Likely to Be Carcinogenic to Humans.'' This descriptor is
appropriate when the weight of the evidence is adequate to demonstrate
carcinogenic
[[Page 17793]]
potential to humans but does not reach the weight of evidence for the
descriptor ``Carcinogenic to Humans.'' Adequate evidence consistent
with this descriptor covers a broad spectrum. As stated previously, the
use of the term ``likely'' as a weight of evidence descriptor does not
correspond to a quantifiable probability. The examples below are meant
to represent the broad range of data combinations that are covered by
this descriptor; they are illustrative and provide neither a checklist
nor a limitation for the data that might support use of this
descriptor. Moreover, additional information, e.g., on mode of action,
might change the choice of descriptor for the illustrated examples.
Supporting data for this descriptor may include:
An agent demonstrating a plausible (but not definitively
causal) association between human exposure and cancer, in most cases
with some supporting biological, experimental evidence, though not
necessarily carcinogenicity data from animal experiments;
An agent that has tested positive in animal experiments in
more than one species, sex, strain, site, or exposure route, with or
without evidence of carcinogenicity in humans;
A positive tumor study that raises additional biological
concerns beyond that of a statistically significant result, for
example, a high degree of malignancy, or an early age at onset;
A rare animal tumor response in a single experiment that
is assumed to be relevant to humans; or
A positive tumor study that is strengthened by other lines
of evidence, for example, either plausible (but not definitively
causal) association between human exposure and cancer or evidence that
the agent or an important metabolite causes events generally known to
be associated with tumor formation (such as DNA reactivity or effects
on cell growth control) likely to be related to the tumor response in
this case.
``Suggestive Evidence of Carcinogenic Potential.'' This descriptor
of the database is appropriate when the weight of evidence is
suggestive of carcinogenicity; a concern for potential carcinogenic
effects in humans is raised, but the data are judged not sufficient for
a stronger conclusion. This descriptor covers a spectrum of evidence
associated with varying levels of concern for carcinogenicity, ranging
from a positive cancer result in the only study on an agent to a single
positive cancer result in an extensive database that includes negative
studies in other species. Depending on the extent of the database,
additional studies may or may not provide further insights. Some
examples include:
A small, and possibly not statistically significant,
increase in tumor incidence observed in a single animal or human study
that does not reach the weight of evidence for the descriptor ``Likely
to Be Carcinogenic to Humans.'' The study generally would not be
contradicted by other studies of equal quality in the same population
group or experimental system (see discussions of conflicting evidence
and differing results, below);
A small increase in a tumor with a high background rate in
that sex and strain, when there is some but insufficient evidence that
the observed tumors may be due to intrinsic factors that cause
background tumors and not due to the agent being assessed. (When there
is a high background rate of a specific tumor in animals of a
particular sex and strain, then there may be biological factors
operating independently of the agent being assessed that could be
responsible for the development of the observed tumors.) In this case,
the reasons for determining that the tumors are not due to the agent
are explained;
Evidence of a positive response in a study whose power,
design, or conduct limits the ability to draw a confident conclusion
(but does not make the study fatally flawed), but where the
carcinogenic potential is strengthened by other lines of evidence (such
as structure-activity relationships); or
A statistically significant increase at one dose only, but
no significant response at the other doses and no overall trend.
``Inadequate Information to Assess Carcinogenic Potential.'' This
descriptor of the database is appropriate when available data are
judged inadequate for applying one of the other descriptors. Additional
studies generally would be expected to provide further insights. Some
examples include:
Little or no pertinent information;
Conflicting evidence, that is, some studies provide
evidence of carcinogenicity but other studies of equal quality in the
same sex and strain are negative. Differing results, that is, positive
results in some studies and negative results in one or more different
experimental systems, do not constitute conflicting evidence, as the
term is used here. Depending on the overall weight of evidence,
differing results can be considered either suggestive evidence or
likely evidence; or
Negative results that are not sufficiently robust for the
descriptor, ``Not Likely to Be Carcinogenic to Humans.''
``Not Likely to Be Carcinogenic to Humans.'' This descriptor is
appropriate when the available data are considered robust for deciding
that there is no basis for human hazard concern. In some instances,
there can be positive results in experimental animals when there is
strong, consistent evidence that each mode of action in experimental
animals does not operate in humans. In other cases, there can be
convincing evidence in both humans and animals that the agent is not
carcinogenic. The judgment may be based on data such as:
Animal evidence that demonstrates lack of carcinogenic
effect in both sexes in well-designed and well-conducted studies in at
least two appropriate animal species (in the absence of other animal or
human data suggesting a potential for cancer effects),
Convincing and extensive experimental evidence showing
that the only carcinogenic effects observed in animals are not relevant
to humans,
Convincing evidence that carcinogenic effects are not
likely by a particular exposure route (see Section 2.3), or
Convincing evidence that carcinogenic effects are not
likely below a defined dose range.
A descriptor of ``not likely'' applies only to the circumstances
supported by the data. For example, an agent may be ``Not Likely to Be
Carcinogenic'' by one route but not necessarily by another. In those
cases that have positive animal experiment(s) but the results are
judged to be not relevant to humans, the narrative discusses why the
results are not relevant.
Multiple Descriptors. More than one descriptor can be used when an
agent's effects differ by dose or exposure route. For example, an agent
may be ``Carcinogenic to Humans'' by one exposure route but ``Not
Likely to Be Carcinogenic'' by a route by which it is not absorbed.
Also, an agent could be ``Likely to Be Carcinogenic'' above a specified
dose but ``Not Likely to Be Carcinogenic'' below that dose because a
key event in tumor formation does not occur below that dose.
2.6. Hazard Characterization
The hazard characterization contains the hazard information needed
for a full risk characterization (U.S. EPA, 2000b). It presents the
results of the hazard assessment and explains how the weight of
evidence conclusion was reached. The hazard characterization
summarizes, in plain language, conclusions about the agent's potential
effects, whether they can be expected to
[[Page 17794]]
depend qualitatively on the circumstances of exposure, and if anyone
can be expected to be especially susceptible. It discusses the extent
to which these conclusions are supported by data or are the result of
default options invoked because the data are inconclusive. It explains
how complex cases with differing results in different studies were
resolved. The hazard characterization highlights the major issues
addressed in the hazard assessment and discusses alternative
interpretations of the data and the degree to which they are
supportable scientifically and are consistent with EPA guidelines.
When the conclusion is supported by mode of action information, the
hazard characterization also provides a clear summary of the mode of
action conclusions (see Section 2.4.3.4), including the completeness of
the data, the strengths and limitations of the inferences made, the
potential for other modes of action, and the implications of the mode
of action for selecting viable approaches to the dose-response
assessment. The hazard characterization also discusses the extent to
which mode of action information is available to address the potential
for disproportionate risks in specific populations or lifestages or the
potential for enhanced risks on the basis of interactions with other
agents or stressors, if anticipated.
Topics that can be addressed in a hazard characterization include:
Summary of the results of the hazard assessment;
Identification of any likely susceptible populations and
lifestages, especially attending to children, infants, and fetuses;
Conclusions about the agent's mode of action, and
implications for selecting approaches to the dose-response assessment;
Identification of the available lines of evidence (e.g.,
animal bioassays, epidemiologic studies, toxicokinetic information,
mode of action studies, and information about structural analogues or
metabolites), highlighting data quality and coherence of results from
different lines of evidence; and
Strengths and limitations of the hazard assessment,
highlighting significant issues in interpreting the data, alternative
interpretations that are considered equally plausible, critical data
gaps, and default options invoked when the available information is
inconclusive.
3. Dose-Response Assessment
Dose-response assessment estimates potential risks to humans at
exposure levels of interest. Dose-response assessments are useful in
many applications: Estimating risk at different exposure levels,
estimating the risk reduction for different decision options,
estimating the risk remaining after an action is taken, providing the
risk information needed for benefit-cost analyses of different decision
options, comparing risks across different agents or health effects, and
setting research priorities. The purpose of the assessment should
consider the quality of the data available, which will vary from case
to case.
A dose-response analysis is generally developed from each study
that reports quantitative data on dose and response. Alternative
measures of dose are available for analyzing human and animal studies
(see Section 3.1). A two-step approach distinguishes analysis of the
dose-response data from inferences made about lower doses. The first
step is an analysis of dose and response in the range of observation of
the experimental or epidemiologic studies (see Section 3.2). Modeling
is encouraged to incorporate a wide range of experimental data into the
dose-response assessment (see Sections 3.1.2, 3.2.1, 3.2.2, 3.2.3). The
modeling yields a point of departure (POD) near the lower end of the
observed range, without significant extrapolation to lower doses (see
Sections 3.2.4, 3.2.5). The second step is extrapolation to lower doses
(see Section 3.3). The extrapolation approach considers what is known
about the agent's mode of action (see Section 3.3.1). Both linear and
nonlinear approaches are available (see Sections 3.3.3, 3.3.4). When
multiple estimates can be developed, the strengths and weaknesses of
each are presented. In some cases, they may be combined in a way that
best represents human cancer risk (see Section 3.3.5). Special
consideration is given to describing dose-response differences
attributable to different human exposure scenarios (see Section 3.4)
and to susceptible populations and lifestages (see Section 3.5). It is
important to discuss significant uncertainties encountered in the
analysis (see Section 3.6) and to characterize other important aspects
of the dose-response assessment (see Section 3.7).
The scope, depth, and use of a dose-response assessment vary in
different circumstances. Although the quality of dose-response data is
not necessarily related to the weight of evidence descriptor, dose-
response assessments are generally completed for agents considered
``Carcinogenic to Humans'' and ``Likely to Be Carcinogenic to Humans.''
When there is suggestive evidence, the Agency generally would not
attempt a dose-response assessment, as the nature of the data generally
would not support one; however, when the evidence includes a well-
conducted study, quantitative analyses may be useful for some purposes,
for example, providing a sense of the magnitude and uncertainty of
potential risks, ranking potential hazards, or setting research
priorities. In each case, the rationale for the quantitative analysis
is explained, considering the uncertainty in the data and the
suggestive nature of the weight of evidence. These analyses generally
would not be considered Agency consensus estimates. Dose-response
assessments are generally not done when there is inadequate evidence,
although calculating a bounding estimate from an epidemiologic or
experimental study that does not show positive results can indicate the
study's level of sensitivity and capacity to detect risk levels of
concern.
Cancer is a collection of several diseases that develop through
cell and tissue changes over time. Dose-response assessment procedures
based on tumor incidence have seldom taken into account the effects of
key precursor events within the whole biological process due to lack of
empirical data and understanding about these events. In this
discussion, response data include measures of key precursor events
considered integral to the carcinogenic process in addition to tumor
incidence. These responses may include changes in DNA, chromosomes, or
other key macromolecules; effects on growth signal transduction,
including induction of hormonal changes; or physiological or toxic
effects that include proliferative events diagnosed as precancerous but
not pathology that is judged to be cancer. Analysis of such responses
may be done along with that of tumor incidence to enhance the tumor
dose-response analysis. If dose-response analysis of nontumor key
events is more informative about the carcinogenic process for an agent,
it can be used in lieu of, or in conjunction with, tumor incidence
analysis for the overall dose-response assessment.
As understanding of mode of action improves and new types of data
become available, dose-response assessment will continue to evolve.
These cancer guidelines encourage the development and application of
new methods that improve dose-response assessment by reflecting new
scientific understanding and new sources of information.
[[Page 17795]]
3.1. Analysis of Dose
For each effect observed, dose-response assessment should begin by
determining an appropriate dose metric. Several dose metrics have been
used, e.g., delivered dose, body burden, and area under the curve, and
others may be appropriate depending on the data and mode of action.
Selection of an appropriate dose metric considers what data are
available and what is known about the agent's mode of action at the
target site, and uncertainties involved in estimation and application
of alternative metrics. The dose metric specifies:
The agent measured, preferably the active agent
(administered agent or a metabolite);
Proximity to the target site (exposure concentration,
potential dose, internal dose, or delivered dose,\5\ reflecting
increasing proximity); and
---------------------------------------------------------------------------
\5\ Exposure is contact of an agent with the outer boundary of
an organism. Exposure concentration is the concentration of a
chemical in its transport or carrier medium at the point of contact.
Dose is the amount of a substance available for interaction with
metabolic processes or biologically significant receptors after
crossing the outer boundary of an organism. Potential dose is the
amount ingested, inhaled, or applied to the skin. Applied dose is
the amount of a substance presented to an absorption barrier and
available for absorption (although not necessarily having yet
crossed the outer boundary of the organism). Absorbed dose is the
amount crossing a specific absorption barrier (e.g., the exchange
boundaries of skin, lung, and digestive tract) through uptake
processes. Internal dose is a more general term, used without
respect to specific absorption barriers or exchange boundaries.
Delivered dose is the amount of the chemical available for
interaction by any particular organ or cell (U.S. EPA, 1992a).
---------------------------------------------------------------------------
The time component of the effective dose (cumulative dose,
average dose, peak dose, or body burden).
Analyses can be based on estimates of animal dose metrics or human
dose metrics. The assessment should describe the approach used to
select a dose metric and the reasons for this approach. The final
analysis, however, should determine a human equivalent dose metric.
This facilitates comparing results from different datasets and effects
by using human equivalent dose/concentrations as common metrics. When
appropriate, it may be necessary to convert dose metrics across
exposure routes. When route-to-route extrapolations are made, the
underlying data, algorithms, and assumptions are clearly described.
Timing of exposure can also be important. When there is a
susceptible lifestage, doses during the susceptible period are not
equivalent to doses at other times, and they would be analyzed
separately.
3.1.1. Standardizing Different Experimental Exposure Regimens
Complex exposure or dosing regimens are often present in
experimental and epidemiologic studies. The resulting internal dose
depends on many variables, including concentration, duration, frequency
of administration, and duration of recovery periods between
administrations. Internal dose also depends on variables that are
intrinsic to the exposed individual, such as lifestage and rates of
metabolism and clearance. To facilitate comparing results from
different study designs and to make inferences about human exposures, a
summary estimate of the dose metric, whether the administered dose or
inhalation exposure concentration or an internal metric, may be derived
for a complex exposure regimen.
Toxicokinetic modeling is the preferred approach for estimating
dose metrics from exposure. Toxicokinetic models generally describe the
relationship between exposure and measures of internal dose over time.
More complex models can reflect sources of intrinsic variation, such as
polymorphisms in metabolism and clearance rates. When a robust model is
not available, or when the purpose of the assessment does not warrant
developing a model, simpler approaches may be used.
For chronic exposure studies, the cumulative exposure or dose
administered often is expressed as an average over the duration of the
study, as one consistent dose metric. This approach implies that a
higher dose administered over a short duration is equivalent to a
commensurately lower dose administered over a longer duration.
Uncertainty usually increases as the duration becomes shorter relative
to the averaging duration or the intermittent doses become more intense
than the averaged dose. Moreover, doses during any specific susceptible
or refractory period would not be equivalent to doses at other times.
For these reasons, cumulative exposure or potential dose may be
replaced by a more appropriate dose metric when indicated by the data.
For mode of action studies, the dose metric should be calculated
over a duration that reflects the time to occurrence of the key
precursor effects. Mode of action studies are often of limited
duration, as the precursors can be observed after less-than-chronic
exposures. When the experimental exposure regimen is specified on a
weekly basis (for example, 4 hours a day, 5 days a week), the daily
exposure may be averaged over the week, where appropriate.
Doses in studies at the cellular or molecular level can be
difficult to relate to organ- or organism-level dose metrics.
Toxicokinetic modeling can sometimes be used to relate doses at the
cellular or molecular level to doses or exposures at higher levels of
organization.
3.1.2. Toxicokinetic Data and Modeling
In the absence of chemical-specific data, physiologically based
toxicokinetic modeling is potentially the most comprehensive way to
account for biological processes that determine internal dose.
Physiologically based models commonly describe blood flow between
physiological compartments and simulate the relationship between
applied dose and internal dose. Toxicokinetic models generally need
data on absorption, distribution, metabolism, and elimination of the
administered agent and its metabolites.
Additionally, in the case of inhalation exposures, models can
explicitly characterize the geometry of the respiratory tract and the
airflow through it, as well as the interaction of this airflow with the
entrained particles or fibers and gases (Kimbell et al., 2001;
Subramaniam et al., 2003). Because of large interspecies differences in
airway morphometry such models can be particularly useful in
interspecies extrapolations. When employed, however, the potential for
large inter-individual differences in airway morphometry, are
considered to ensure that the models provide information representative
of human populations.
Toxicokinetic models can improve dose-response assessment by
revealing and describing nonlinear relationships between applied and
internal dose. Nonlinearity observed in a dose-response curve often can
be attributed to toxicokinetics (Hoel et al., 1983; Gaylor et al.,
1994), involving, for example, saturation or induction of enzymatic
processes at high doses. In some cases, toxicokinetic processes tend to
become linear at sufficiently low doses (Hattis, 1990).
A discussion of confidence should accompany the presentation of
model results and include consideration of model validation and
sensitivity analysis, stressing the predictive performance of the model
and whether the model is sufficient to support decision-making.
Quantitative uncertainty analysis is important for evaluating the
performance of a model, whether the model is based primarily on default
assumptions or chemical-specific data. The uncertainty analysis covers
questions of model uncertainty
[[Page 17796]]
(e.g., Is the model based on the appropriate biology and how does that
affect estimates of dose metrics?) and parameter uncertainty (e.g., Do
the data support unbiased and stable estimates of the model
parameters?). When a delivered dose measure is used in animal-to-human
extrapolation, the assessment discusses the confidence of the target
tissue and its toxicodynamics being the same in both species (see
Section 3.6). Toxicokinetic modeling results may be presented alone as
the preferred method of estimating human equivalent exposures or doses,
or these results may be presented in parallel with default procedures
(see Section 3.1.3), depending on the confidence in the modeling.
3.1.3. Cross-Species Scaling Procedures
Standard cross-species scaling procedures are available when the
data are not sufficient to support a toxicokinetic model or when the
purpose of the assessment does not warrant developing one. The aim is
to define exposure levels for humans and animals that are expected to
produce the same degree of effect (U.S. EPA, 1992b), taking into
account differences in scale between test animals and humans, such as
size and lifespan.
3.1.3.1. Oral Exposures
For oral exposures, administered doses should be scaled from
animals to humans on the basis of equivalence of mg/kg3/4-d
(milligrams of the agent normalized by the \3/4\ power of body weight
per day) (U.S. EPA, 1992b). The \3/4\ power is consistent with current
science, including empirical data that allow comparison of potencies in
humans and animals, and it is also supported by analysis of the
allometric variation of key physiological parameters across mammalian
species. It is generally more appropriate at low doses, where sources
of nonlinearity such as saturation of enzyme activity are less likely
to occur. This scaling is intended as an unbiased estimate rather than
a conservative one. Equating exposure concentrations in food or water
is an alternative version of the same approach, because daily intakes
of food or water are approximately proportional to the \3/4\ power of
body weight.
The aim of these cross-species scaling procedures is to estimate
administered doses in animals and humans that result in equal lifetime
risks. It is useful to recognize two components of this equivalence:
toxicokinetic equivalence, which determines administered doses in
animals and humans that yield equal tissue doses, and toxicodynamic
equivalence, which determines tissue doses in animals and humans that
yield equal lifetime risks (U.S. EPA, 1992b). Toxicokinetic modeling
(see Section 3.1.2) addresses factors associated with toxicokinetic
equivalence, and toxicodynamic modeling (see Section 3.2.2) addresses
factors associated with toxicodynamic equivalence. When toxicokinetic
modeling is used without toxicodynamic modeling, the dose-response
assessment develops and supports an approach for addressing
toxicodynamic equivalence, perhaps by retaining some of the cross-
species scaling factor (e.g., using the square root of the cross-
species scaling factor or using a factor of 3 to cover toxicodynamic
differences between animals and humans, as is currently done in
deriving inhalation reference concentrations [U.S. EPA, 1994]).
When assessing risks from childhood exposure, the mg/
kg3/4-d scaling factor does not use the child's body weight
(U.S. EPA, 1992b). This reflects several uncertainties in extrapolating
risks to children:
The data supporting the mg/kg3/4-d scaling
factor were derived for differences across species and may not apply as
well to differently sized individuals of the same species or to
different lifestages.
In addition to metabolic differences, there are also
important toxicodynamic differences; for example, children have faster
rates of cell division than do adults, so scaling across different
lifestages and species simultaneously may be particularly uncertain.
3.1.3.2. Inhalation Exposures
For inhalation exposures experimental exposure concentrations are
replaced with human equivalent concentrations calculated using EPA's
methods for deriving inhalation reference concentrations (U.S. EPA,
1994), which give preference to the use of toxicokinetic modeling. When
toxicokinetic models are unavailable, default dosimetry models are
employed to extrapolate from experimental exposure concentrations to
human equivalent concentrations. When toxicokinetic modeling or
dosimetry modeling is used without toxicodynamic modeling, the dose-
response assessment develops and supports an approach for addressing
toxicodynamic equivalence.
The default dosimetry models typically involve the use of species-
specific physiologic and anatomic factors relevant to the form of the
agent (e.g., particle or gas) and categorized with regard to whether
the response occurs either locally (i.e., within the respiratory tract)
or remotely. For example, current default models (U.S. EPA, 1994) use
parameters such as:
Inhalation rate and surface area of the affected part of
the respiratory tract for gases eliciting the response locally,
Blood:gas partition coefficients for remote acting gases,
Fractional deposition with inhalation rate and surface
area of the affected part of the respiratory tract for particles
eliciting the response locally, and
Fractional deposition with inhalation rate and body weight
for particles eliciting the response remotely.
The current default values for some parameters used in the default
models (e.g., breathing rate and respiratory tract surface area) are
based on data from adults (U.S. EPA, 1994). The human respiratory
system passes through several distinct stages of maturation and growth
during the first several years of life and into adolescence (Pinkerton
and Joad, 2000), during which characteristics important to disposition
of inhaled toxicants may vary. Children and adults breathing the same
concentration of an agent may receive different doses to the body or
lungs (U.S. EPA, 2002b). Consequently, it may be appropriate to
evaluate the default models by considering physiologic and anatomic
factors representative of early lifestages, for example through the
substitution of child-specific parameters (U.S. EPA, 2002b). Such
evaluation uses the default model and dosimetric adjustment in use at
the time of the assessment coupled with the best understanding of
child-specific parameters at that time (e.g., drawn from the scientific
literature). This analysis is undertaken with caution: (1) because of
the correlations between activity level, breathing rate, respiratory
tract dimensions, and body weight and (2) to avoid the possibility of
mismatching the type of agent (gas or particle) and its site of
response (within the respiratory tract or remote from the respiratory
tract) with the relevant dosimetry factors in use at the time of the
assessment. Analyses of children's inhalation dosimetry are also
considered when using model structures beyond the default models (e.g.,
physiologically based toxicokinetic models).
When using dosimetry modeling, the comparison of human-equivalent
concentrations for different lifestages (e.g., for an adult and a
child) can indicate whether it is important to carry both
concentrations forward in the dose-response assessment or whether a
verbal characterization of any findings will suffice.
[[Page 17797]]
3.1.4. Route Extrapolation
In certain situations, an assessment based on studies of one
exposure route may be applied to another exposure route. Route-to-route
extrapolation has both qualitative and quantitative aspects. For the
qualitative aspect, the assessor should weigh the degree to which
positive results by one exposure route support a judgment that similar
results would be expected by another route. In general, confidence in
making such a judgment is strengthened when tumors are observed at a
site distant from the portal of entry and when absorption is similar
through both routes. In the absence of contrary data, a qualitative
default option can be used: If the agent is absorbed through an
exposure route to give an internal dose, it may be carcinogenic by that
route.
When a qualitative extrapolation can be supported, quantitative
extrapolation may still be problematic due to the absence of adequate
data. The differences in biological processes among routes of exposure
(oral, inhalation, dermal) can be great because of, for example, first-
pass effects and different results from different exposure patterns.
There is no generally applicable method for accounting for these
differences in uptake processes in a quantitative route-to-route
extrapolation of dose-response data in the absence of good data on the
agent of interest. Therefore, route-to-route extrapolation of dose data
relies on a case-by-case analysis of available data. When good data on
the agent itself are limited, an extrapolation analysis can be based on
expectations from physical and chemical properties of the agent,
properties and route-specific data on structurally analogous compounds,
or in vitro or in vivo uptake data on the agent.
Route-to-route uptake models may be applied if model parameters are
suitable for the compound of interest. Such models are currently
considered interim methods; further model development and validation is
awaiting the development of more extensive data. For screening or
hazard ranking, route-to-route extrapolation may be based on assumed
quantitative comparability as a default, as long as it is reasonable to
assume absorption by compared routes. When route-to-route extrapolation
is used, the assessor's degree of confidence in both the qualitative
and quantitative extrapolation is discussed in the assessment and
highlighted in the dose-response characterization.
Toxicokinetic modeling can be used to compare results of studies by
different exposure routes. Results can also be compared on the basis of
internal dose for effects distant from the point of contact.
Route extrapolation can be used to understand how internal dose and
subsequent effects depend on exposure route. If testing by different
exposure routes is available, the observation of similar or dissimilar
internal doses can be important in determining whether and what
conclusions can be made concerning the dose-response function(s) for
different routes of exposure.
3.2. Analysis in the Range of Observation
The principle underlying these cancer guidelines is to use
approaches that include as much information as possible. Quantitative
information about key precursor events can be used to develop a
toxicodynamic model. Alternatively, such information can be fitted by
empirical models to extend the dose-response analysis of tumor
incidence to lower doses and response levels. The analysis in the range
of observation is used to establish a POD near the lower end of the
observed range (see Section 3.3).
3.2.1. Epidemiologic Studies
Ideally, epidemiologic data would be used to select the dose-
response function for human exposures. Because epidemiologic data are
usually limited and many models may fit the data (Samet et al.,1998),
other factors may influence model choice. For epidemiologic studies,
including those with grouped data, analysis by linear models in the
range of observation is generally appropriate unless the fit is poor.
The relatively small exposure range observed in many epidemiologic
studies, for example, makes it difficult to discern the shape of the
exposure-or dose-response curve. Exposure misclassification and errors
in exposure estimation also obscure the shape of the dose-response
curve. When these errors are unsystematic or random, the result is
frequently to bias the risk estimates toward zero. When a linear model
fits poorly, more flexible models that allow for low-dose linearity,
for example, a linear-quadratic model or a Hill model (Murrell et al.,
1998), are often considered next.
Analysis of epidemiologic studies depends on the type of study and
quality of the data, particularly the availability of quantitative
measures of exposure. The objective is to develop a dose-response curve
that estimates the incidence of cancer attributable to the dose (as
estimated from the exposure) to the agent. In some cases, e.g., tobacco
smoke or occupational exposures, the data are in the range of the
exposures of interest. In other cases, as with data from animal
experiments, information from the observable range is extrapolated to
exposures of interest.
Analysis of effects raises additional issues:
Many studies collect information from death certificates,
which leads to estimates of mortality rather than incidence. Because
survival rates vary for different cancers, the analysis may be improved
by adjusting mortality figures to reflect the relationship between
incidence and mortality.
Epidemiologic studies, by their nature, are limited in the
extent to which they can control for effects due to exposures from
other agents. In some cases, the agent can have discernible interactive
effects with another agent, making it possible to estimate the
contribution of each agent as a risk factor for the effects of the
other. For example, competing risks in a study population can limit the
observed occurrence of cancer, while additive effects may lead to an
increase occurrence of cancer. In the case of rates not already so
adjusted, the analysis can be improved by correcting for competing or
additive risks that are not similar in exposed and comparison groups.
Comparison groups that are not free from exposure to the
agent can bias the risk estimates toward zero. The analysis can be
improved by considering background exposures in the exposed and
comparison groups.
The latent period for most cancers implies that exposures
immediately preceding the detection of a tumor would be less likely to
have contributed to its development and, therefore, may count less in
the analysis. Study subjects who were first exposed near the end of the
study may not have had adequate time since exposure for cancer to
develop; therefore, analysis of their data may be similar to analysis
of data for those who were not exposed. However, for carcinogens that
act on multiple stages of the carcinogenic process, especially the
later stages, all periods of exposure. including recent exposures, may
be important.
Some study designs can yield only a partial characterization of the
overall hazard and therefore risk as, for example, in studies that: (1)
investigate only one effect (typical of many case-control studies), (2)
include only one population segment (e.g., male workers or workers of
one socioeconomic class), or (3) include only one lifestage (e.g.,
childhood leukemia following maternal exposure to contaminated drinking
water). To obtain a more complete
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characterization that includes risks of other cancers, estimates from
these studies can be supplemented with estimates from other studies
that investigated other cancers, population segments, or lifestages
(see Section 3.5).
When several studies are available for dose-response analysis,
meta-analysis can provide a systematic approach to weighing positive
studies and those studies that do not show positive results, and
calculating an overall risk estimate with greater precision. Issues
considered include the comparability of studies, heterogeneity across
studies, and the potential for a single large study to dominate the
analysis. Confidence in a meta-analysis is increased when it considers
study quality, including definition of the study population and
comparison group, measurement of exposure, potential for exposure
misclassification, adequacy of follow-up period, and analysis of
confounders (see Section 2.2.1.3).
3.2.2. Toxicodynamic (``Biologically Based'') Modeling
Toxicodynamic modeling can be used when there are sufficient data
to ascertain the mode of action (see Section 2.4) and quantitatively
support model parameters that represent rates and other quantities
associated with the key precursor events of the mode of action.
Toxicodynamic modeling is potentially the most comprehensive way to
account for the biological processes involved in a response. Such
models seek to reflect the sequence of key precursor events that lead
to cancer. Toxicodynamic models can contribute to dose-response
assessment by revealing and describing nonlinear relationships between
internal dose and cancer response. Such models may provide a useful
approach for analysis in the range of observation, provided the purpose
of the assessment justifies the effort involved.
If a new model is developed for a specific agent, extensive data on
the agent are important for identifying the form of the model,
estimating its parameters, and building confidence in its results.
Conformance to the observed tumor incidence data alone does not
establish a model's validity, as a model can be designed with a
sufficiently large number of parameters so as to fit any given dataset.
Peer review, including both an examination of the scientific basis
supporting the model and an independent evaluation of the model's
performance, is an essential part of evaluating the new model.
If a standard model already exists for the agent's mode of action,
the model can be adapted for the agent by using agent-specific data to
estimate the model's parameters. An example is the two-stage clonal
expansion model developed by Moolgavkar and Knudson (1981) and Chen and
Farland (1991). These models continue to be improved as more
information becomes available.
It is possible for different models to provide equivalent fits to
the observed data but to diverge substantially in their projections at
lower doses. When model parameters are estimated from tumor incidence
data, it is often the case that different combinations of parameter
estimates can yield similar results in the observed range. For this
reason, critical parameters (e.g., mutation rates and cell birth and
death rates) are estimated from laboratory studies and not by curve-
fitting to tumor incidence data (Portier, 1987). This approach reduces
model uncertainty (see Section 3.6) and ensures that the model does not
give answers that are biologically unrealistic. This approach also
provides a robustness of results, where the results are not likely to
change substantially if fitted to slightly different data.
Toxicodynamic modeling can provide insight into the relationship
between tumors and key precursor events. For example, a model that
includes cell proliferation can be used to explore the extent to which
small increases in the cell proliferation rate can lead to large
lifetime tumor incidences (Gaylor and Zheng, 1996). In this way,
toxicodynamic modeling can be used to select and characterize an
appropriate precursor response level (see Section 3.2.2, 3.2.5).
3.2.3. Empirical Modeling (``Curve Fitting'')
When a toxicodynamic model is not available or when the purpose of
the assessment does not warrant developing such a model, empirical
modeling (sometimes called ``curve fitting'') should be used in the
range of observation. A model can be fitted to data on either tumor
incidence or a key precursor event. Goodness-of-fit to the experimental
observations is not by itself an effective means of discriminating
among models that adequately fit the data (OSTP, 1985). Many different
curve-fitting models have been developed, and those that fit the
observed data reasonably well may lead to several-fold differences in
estimated risk at the lower end of the observed range. Another problem
occurs when a multitude of alternatives are presented without
sufficient context to make a reasoned judgment about the alternatives.
This form of model uncertainty reflects primarily the availability of
different computer models and not biological information about the
agent being assessed or about carcinogenesis in general. In cases where
curve-fitting models are used because the data are not adequate to
support a toxicodynamic model, there generally would be no biological
basis to choose among alternative curve-fitting models. However, in
situations where there are alternative models with significant
biological support, the decisionmaker can be informed by the
presentation of these alternatives along with their strengths and
uncertainties.
Quantitative data on precursors can be used in conjunction with, or
in lieu of, data on tumor incidence to extend the dose-response curve
to lower doses. Caution is used with rates of molecular events such as
mutation or cell proliferation or signal transduction. Such rates can
be difficult to relate to cell or tissue changes overall. The timing of
observations of these phenomena, as well as the cell type involved, is
linked to other precursor events to ensure that the measurement is
truly a key event (Section 2.4).
For incidence data on either tumors or a precursor, an established
empirical procedure is used to provide objectivity and consistency
among assessments. The procedure models incidence, corrected for
background, as an increasing function of dose. The models are
sufficiently flexible in the observed range to fit linear and nonlinear
datasets. Additional judgments and perhaps alternative analyses are
used when the procedure fails to yield reliable results. For example,
when a model's fit is poor, the highest dose is often omitted in cases
where it is judged that the highest dose reflects competing toxicity
that is more relevant at high doses than at lower doses. Another
example is when there are large differences in survival across dose
groups; here, models that includes time-to-tumor or time-to-event
information may be useful.
For continuous data on key precursor effects, empirical models can
be chosen on the basis of the structure of the data. The rationale for
the choice of model, the alternatives considered and rejected, and a
discussion of model uncertainty are included in the dose-response
characterization.
3.2.4. Point of Departure (POD)
For each tumor response, a POD from the observed data should be
estimated to mark the beginning of extrapolation to lower doses. The
POD is an estimated dose (expressed in human-equivalent terms) near the
lower end of the observed range without significant extrapolation to
lower doses.
[[Page 17799]]
The POD is used as the starting point for subsequent extrapolations
and analyses. For linear extrapolation, the POD is used to calculate a
slope factor (see Section 3.3.3), and for nonlinear extrapolation the
POD is used in the calculation of a reference dose or reference
concentration (see Section 3.3.4). In a risk characterization, the POD
is part of the determination of a margin of exposure (see Section 5.4).
With appropriate adjustments, it can also be used as the basis for
hazard rankings that compare different agents or health effects.
The lowest POD is used that is adequately supported by the data. If
the POD is above some data points, it can fail to reflect the shape of
the dose-response curve at the lowest doses and can introduce bias into
subsequent extrapolations (see Figure 3-1). On the other hand, if the
POD is far below all observed data points, it can introduce model
uncertainty and parameter uncertainty (see Section 3.6) that increase
with the distance between the data and the POD. Use of a POD at the
lowest level supported by the data seeks to balance these
considerations. It uses information from the model(s) a small distance
below the observed range rather than discarding this information and
using extrapolation procedures in a range where the model(s) can
provide some useful information. Statistical tests involving the ratio
of the central estimate and its lower bound (i.e., EDxx/
LEDxx) can be useful for evaluating how well the data
support a model's estimates at a particular response level. (Note that
the ability to model at a particular response level is not the same as
the study's ability to identify an increase at that response level as
statistically significant.)
The POD for extrapolating the relationship to environmental
exposure levels of interest, when the latter are outside the range of
observed data, is generally the lower 95% confidence limit on the
lowest dose level that can be supported for modeling by the data. SAB
(1997) suggested that, ``it may be appropriate to emphasize lower
statistical bounds in screening analyses and in activities designed to
develop an appropriate human exposure value, since such activities
require accounting for various types of uncertainties and a lower bound
on the central estimate is a scientifically-based approach accounting
for the uncertainty in the true value of the ED10 [or
central estimate].'' However, the consensus of the SAB (1997) was that,
``both point estimates and statistical bounds can be useful in
different circumstances, and recommended that the Agency routinely
calculate and present the point estimate of the ED10 [or
central estimate] and the corresponding upper and lower 95% statistical
bounds.'' For example, it may be appropriate to emphasize the central
estimate in activities that involve formal uncertainty analysis that
are required by OMB Circular A-4 (OMB, 2003) as well as ranking agents
as to their carcinogenic hazard. Thus, risk assessors should calculate,
to the extent practicable, and present the central estimate and the
corresponding upper and lower statistical bounds (such as confidence
limits) to inform decisionmakers.
When tumor data are used, a POD is obtained from the modeled tumor
incidences. Conventional cancer bioassays, with approximately 50
animals per group, generally can support modeling down to an increased
incidence of 1-10%; epidemiologic studies, with larger sample sizes,
below 1%. Various models commonly used for carcinogens yield similar
estimates of the POD at response levels as low as 1% (Krewski and Van
Ryzin, 1981; Gaylor et al., 1994). Consequently, response levels at or
below 10% can often be used as the POD. As a modeling convention, the
lower bound on the doses associated with standard response levels of 1,
5, and 10% can be analyzed, presented, and considered. For making
comparisons at doses within the observed range, the ED10 and
LED10 are also reported and can be used, with appropriate
adjustments, in hazard rankings that compare different agents or health
effects (U.S. EPA, 2002c). A no-observed-adverse-effect level (NOAEL)
generally is not used for assessing the potential for carcinogenic
response when one or more models can be fitted to the data.
When good quality precursor data are available and are clearly tied
to the mode of action of the compound of interest, models that include
both tumors and their precursors may be advantageous for deriving a
POD. Such models can provide insight into quantitative relationships
between tumors and precursors (see Section 3.2.2), possibly suggesting
the precursor response level that is associated with a particular tumor
response level. The goal is to use precursor data to extend the
observed range below what can be observed in tumor studies. EPA is
continuing to examine this issue and anticipates that findings and
conclusions may result in supplemental guidance to these cancer
guidelines. If the precursor data are drawn from small samples or if
the quantitative relationship between tumors and precursors is not well
defined, then the tumor data will provide a more reliable POD.
Precursor effects may or may not be biologically adverse in themselves;
the intent is to consider not only tumors but also damage that can lead
to subsequent tumor development by the agent. Analysis of continuous
data may differ from discrete data; Murrell et al. (1998) discuss
alternative approaches to deriving a POD from continuous data.
3.2.5. Characterizing the POD: The POD Narrative
As a single-point summary of a single dose-response curve, the POD
alone does not convey all the critical information present in the data
from which it is derived. To convey a measure of uncertainty, the POD
should be presented as a central estimate with upper and lower bounds.
A POD narrative summarizes other important features of the database and
the POD that are important to account for in low-dose extrapolations or
other analyses.
(a) Nature of the response. Is the POD based on tumors or a
precursor? If on tumors, does the POD measure incidence or mortality?
Is it a lifetime measure or was the study terminated early? The
relationships between precursors and tumors, incidence and mortality,
and lifetime and early-termination results vary from case to case.
Modeling can provide quantitative insight into these relationships, for
example, linking a change in a precursor response to a tumor incidence
(see Section 3.2.2). This can aid in evaluating the significance of the
response at the POD and adjusting different PODs to make them
comparable.
(b) Level of the response. What level of response is associated
with the POD, for example, 1% cancer risk, 10% cancer risk, or 10%
change in a precursor measure?
(c) Nature of the study population. Is the POD based on humans or
animals? How large is the effective sample size? Is the study group
representative of the general population, of healthy adult workers, or
of a susceptible group? Are both sexes represented? Did exposure occur
during a susceptible lifestage?
(d) Slope of the dose-response curve at the POD. How does response
change as dose is reduced below the POD? A steep slope indicates that
risk decreases rapidly as dose decreases. On the other hand, a steep
slope also indicates that errors in an exposure assessment can lead to
large errors in estimating risk. Both aspects of the slope are
important. The slope also indicates whether dose-response curves for
different effects are likely to cross below the POD. For example, in
the ED01 study where 2-
[[Page 17800]]
acetylaminofluorene caused bladder carcinomas and liver carcinomas in
mice (Littlefield et al., 1980), the dose-response curves for these
tumors cross between 10% and 1% response (see Figure 3-2). This
crossing, which can be inferred from the slopes of the curves at a 10%
response, shows how considering the slope can lead to better inferences
about the predominant effects expected at lower doses. Mode of action
data can also be useful; quantitative information about key precursor
events can be used to describe how risk decreases as dose decreases
below the POD.
(e) Relationship of the POD with other cancers. How does the POD
for this cancer relate to PODs for other cancers observed in the
database? For example, a POD based on male workers would not reflect
the implications of mammary tumors in female rats or mice.
(f) Extent of the overall cancer database. Have potential cancer
responses been adequately studied (e.g., were all tissues examined), or
is the database limited to particular effects, population segments, or
lifestages? Do the mode of action data suggest a potential for cancers
not observed in the database (e.g., disruption of particular endocrine
pathways leading to related cancers)?
3.2.6. Relative Potency Factors
Relative potency factors (of which toxicity equivalence factors are
a special case) can be used for a well-defined class of agents that
operate through a common mode of action for the same toxic endpoint. A
complete dose-response assessment is conducted for one well-studied
member of the class that serves as the index chemical for the class.
The other members of the class are tied to the index chemical by
relative potency factors that are based on characteristics such as
relative toxicological outcomes, relative metabolic rates, relative
absorption rates, quantitative SARs, or receptor binding
characteristics (U.S. EPA, 2000c). Examples of this approach are the
toxicity equivalence factors for dioxin-like compounds and the relative
potency factors for some carcinogenic polycyclic aromatic hydrocarbons.
Whenever practicable, toxicity equivalence factors should be validated
and accompanied by quantitative uncertainty analysis.
3.3. Extrapolation to Lower Doses
The purpose of low-dose extrapolation is to provide as much
information as possible about risk in the range of doses below the
observed data. The most versatile forms of low-dose extrapolation are
dose-response models that characterize risk as a probability over a
range of environmental exposure levels. These risk probabilities allow
estimates of the risk reduction under different decision options and
estimates of the risk remaining after an action is taken and provide
the risk information needed for benefit-cost analyses of different
decision options.
When a dose-response model is not developed for lower doses,
another form of low-dose extrapolation is a safety assessment that
characterizes the safety of one lower dose, with no explicit
characterization of risks above or below that dose. Although this type
of extrapolation may be adequate for evaluation of some decision
options, it may not be adequate for other purposes (e.g., benefit-cost
analyses) that require a quantitative characterization of risks across
a range of doses. At this time, safety assessment is the default
approach for tumors that arise through a nonlinear mode of action;
however, EPA continues to explore methods for quantifying dose-response
relationships over a range of environmental exposure levels for tumors
that arise through a nonlinear mode of action (U.S. EPA, 2002c). EPA
program offices that need this more explicit dose-response information
may develop and apply methods that are informed by the methods
described in these cancer guidelines.
3.3.1. Choosing an Extrapolation Approach
The approach for extrapolation below the observed data considers
the understanding of the agent's mode of action at each tumor site (see
Section 2.4). Mode of action information can suggest the likely shape
of the dose-response curve at lower doses. The extent of inter-
individual variation is also considered, with greater variation
spreading the response over a wider range of doses.
Linear extrapolation should be used when there are MOA data to
indicate that the dose-response curve is expected to have a linear
component below the POD. Agents that are generally considered to be
linear in this region include:
Agents that are DNA-reactive and have direct mutagenic
activity, or
Agents for which human exposures or body burdens are high
and near doses associated with key precursor events in the carcinogenic
process, so that background exposures to this and other agents
operating through a common mode of action are in the increasing,
approximately linear, portion of the dose-response curve.
When the weight of evidence evaluation of all available data are
insufficient to establish the mode of action for a tumor site and when
scientifically plausible based on the available data, linear
extrapolation is used as a default approach, because linear
extrapolation generally is considered to be a health-protective
approach. Nonlinear approaches generally should not be used in cases
where the mode of action has not been ascertained. Where alternative
approaches with significant biological support are available for the
same tumor response and no scientific consensus favors a single
approach, an assessment may present results based on more than one
approach.
A nonlinear approach should be selected when there are sufficient
data to ascertain the mode of action and conclude that it is not linear
at low doses and the agent does not demonstrate mutagenic or other
activity consistent with linearity at low doses. Special attention is
important when the data support a nonlinear mode of action but there is
also a suggestion of mutagenicity. Depending on the strength of the
suggestion of mutagenicity, the assessment may justify a conclusion
that mutagenicity is not operative at low doses and focus on a
nonlinear approach, or alternatively, the assessment may use both
linear and nonlinear approaches.
Both linear and nonlinear approaches may be used when there are
multiple modes of action. If there are multiple tumor sites, one with a
linear and another with a nonlinear mode of action, then the
corresponding approach is used at each site. If there are multiple
modes of action at a single tumor site, one linear and another
nonlinear, then both approaches are used to decouple and consider the
respective contributions of each mode of action in different dose
ranges. For example, an agent can act predominantly through
cytotoxicity at high doses and through mutagenicity at lower doses
where cytotoxicity does not occur. Modeling to a low response level can
be useful for estimating the response at doses where the high-dose mode
of action would be less important.
3.3.2. Extrapolation Using a Toxicodynamic Model
The preferred approach is to develop a toxicodynamic model of the
agent's mode of action and use that model for extrapolation to lower
doses (see Section 3.2.2). The extent of extrapolation is governed by
an analysis of model uncertainty, where alternative models that fit
similarly in the observed
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range can diverge below that range (see Section 3.6). Substantial
divergence is likely when model parameters are estimated from tumor
incidence data, so that different combinations of parameter estimates
yield similar fits in the observed range but have different
implications at lower doses. An analysis of model uncertainty can be
used to determine the range where extrapolation using the toxicodynamic
model is supported and where further extrapolation would be based on
either a linear or a nonlinear default, as appropriate (see Sections
3.3.3, 3.3.4).
3.3.3. Extrapolation Using a Low-Dose, Linear Model
Linear extrapolation should be used in two distinct circumstances:
(1) When there are data to indicate that the dose-response curve has a
linear component below the POD, or (2) as a default for a tumor site
where the mode of action is not established (see Section 3.3.1). For
linear extrapolation, a line should be drawn from the POD to the
origin, corrected for background. This implies a proportional (linear)
relationship between risk and dose at low doses. (Note that the dose-
response curve generally is not linear at higher doses.)
The slope of this line, known as the slope factor, is an upper-
bound estimate of risk per increment of dose that can be used to
estimate risk probabilities for different exposure levels. The slope
factor is equal to 0.01/LED01 if the LED01 is
used as the POD.
Unit risk estimates express the slope in terms of [mu]g/L drinking
water or [mu]g/m3 or ppm air. In general, the drinking water
unit risk is derived by converting a slope factor from units of mg/kg-d
to units of [mu]g/L, whereas an inhalation unit risk is developed
directly from a dose-response analysis using equivalent human
concentrations already expressed in units of [mu]g/m3. Unit
risk estimates often assume a standard intake rate (L/day drinking
water or m3/day air) and body weight (kg), which may need to
be reconciled with the exposure factors for the population of interest
in an exposure assessment (see Section 4.4). Alternatively, when the
slope factor for inhalation is in units of ppm, it may sometimes be
termed the inhalation unit risk. Although unit risks have not been
calculated in the past for dermal exposures, both exposures that are
absorbed into the systemic circulation and those that remain in contact
with the skin are also important.
Risk-specific doses are derived from the slope factor or unit risk
to estimate the dose associated with a specific risk level, for
example, a one-in-a-million increased lifetime risk.
3.3.4. Nonlinear Extrapolation to Lower Doses
A nonlinear extrapolation method can be used for cases with
sufficient data to ascertain the mode of action and to conclude that it
is not linear at low doses but with not enough data to support a
toxicodynamic model that may be either nonlinear or linear at low
doses. Nonlinear extrapolation having a significant biological support
may be presented in addition to a linear approach when the available
data and a weight of evidence evaluation support a nonlinear approach,
but the data are not strong enough to ascertain the mode of action
applying the Agency's mode of action framework. If the mode of action
and other information can support chemical-specific modeling at low
doses, it is preferable to default procedures.
For cases where the tumors arise through a nonlinear mode of
action, an oral reference dose or an inhalation reference
concentration, or both, should be developed in accordance with EPA's
established practice for developing such values, taking into
consideration the factors summarized in the characterization of the POD
(see Section 3.2.5). This approach expands the past focus of such
reference values (previously reserved for effects other than cancer) to
include carcinogenic effects determined to have a nonlinear mode of
action. As with other health effects of concern, it is important to put
cancer in perspective with the overall health impact of an exposure by
comparing reference value calculations for cancer with those for other
health effects.
For effects other than cancer, reference values have been described
as being based on the assumption of biological thresholds. The Agency's
more current guidelines for these effects (U.S. EPA, 1996a, 1998b),
however, do not use this assumption, citing the difficulty of
empirically distinguishing a true threshold from a dose-response curve
that is nonlinear at low doses.
Economic and policy analysts need to know how the probability of
cancer varies at exposures above the reference value and whether, and
to what extent, there are health benefits from reducing exposures below
the reference value. The risk assessment community is working to
develop better methods to provide more useful information to economic
and policy analysts.
3.3.5. Comparing and Combining Multiple Extrapolations
When multiple estimates can be developed, all datasets should be
considered and a judgment made about how best to represent the human
cancer risk. Some options for presenting results include:
Adding risk estimates derived from different tumor sites
(NRC, 1994),
Combining data from different datasets in a joint analysis
(Putzrath and Ginevan, 1991; Stiteler et al., 1993; Vater et al.,
1993),
Combining responses that operate through a common mode of
action,
Representing the overall response in each experiment by
counting animals with any tumor showing a statistically significant
increase,
Presenting a range of results from multiple datasets (in
this case, the dose-response assessment includes guidance on how to
choose an appropriate value from the range),
Choosing a single dataset if it can be justified as most
representative of the overall response in humans, or
A combination of these options.
Cross-comparison of estimates from human and animal studies can
provide a valuable risk perspective.
Calculating an animal-derived slope factor and using it to
estimate the risk expected in a human study can provide information
with which to evaluate the human study design, for example, adequacy of
exposure level and sample size.
Calculating an upper-bound slope factor from a human study
that does not show positive results but that has good exposure
information, and comparing it to an animal-derived slope factor can
indicate whether the animal and humans studies are consistent.
3.4. Extrapolation to Different Human Exposure Scenarios
As described in the previous cancer guidelines, special problems
arise when the human exposure situation of concern suggests exposure
regimens, e.g., route and dosing schedule, that are substantially
different from those used in the relevant animal studies. Unless there
is evidence to the contrary in a particular case, the cumulative dose
received over a lifetime, expressed as average daily exposure prorated
over a lifetime, is recommended as an appropriate measure of exposure
to a carcinogen. That is, the assumption is made that a high dose of a
carcinogen received over a short period of time is equivalent to a
corresponding low dose spread over a lifetime. This approach becomes
more problematical as the exposures in question become more intense but
less frequent, especially when there is evidence that the agent has
shown dose-rate effects (U.S. EPA 1986a).
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Accordingly, for lifetime human exposure scenarios that involve
intermittent or varying levels of exposure, the prevailing practice has
been to assess exposure by calculating a lifetime average daily
exposure or dose (U.S. EPA, 1992a).
For less-than-lifetime human exposure scenarios, too, the lifetime
average daily exposure or dose has often been used. The use of these
lifetime average exposure metrics was adopted with low-dose linear
cancer assessments in mind. The lifetime averaging implies that less-
than-lifetime exposure is associated with a linearly proportional
reduction of the lifetime risk, regardless of when exposures occur.
Such averaging may be problematic in some situations. This can be
illustrated using both the multistage model and the two-stage clonal
expansion model that predict that short-duration risks are not
necessarily proportional to exposure duration and can depend on the
nature of the carcinogen and the timing of exposure (Goddard et al.,
1995; Murdoch et al., 1992). These examples indicate some circumstances
in which use of a lifetime average daily dose (LADD) would
underestimate cancer risk by two-to fivefold, and others in which it
might overestimate risk (Murdoch et al., 1992). Thus, averaging over
the duration of a lifestage or a critical window of exposure may be
appropriate. As methodological research focuses on new approaches for
estimating risks from less-than-lifetime exposures, methods and
defaults can be expected to change.
This highlights the importance for each dose-response assessment to
critically evaluate all information pertaining to less-than-lifetime
exposure. For example, detailed stop-exposure studies can provide
information about the relationship between exposure duration, precursor
effects, potential for reversibility, and tumor development.
Toxicokinetic modeling can investigate differences in internal dose
between short-term and long-term exposure or between intermittent and
constant exposure. Persistence in the body can be useful in explaining
long-term effects resulting from shorter-term exposures.
For nonlinear cancer analyses, it may be appropriate to assess
exposure by calculating a daily dose that is averaged over the exposure
duration for the study (see Section 3.1.1). For example, when the
analysis is based on precursor effects that result from less than a
lifetime exposure, that exposure period may be used. This reflects an
expectation that the precursor effects on which the analysis is based
can result from less-than-lifetime exposure, bringing consistency to
the methods used for dose-response assessment and exposure assessment
in such cases. The dose-response assessment can provide a
recommendation to exposure assessors about the averaging time that is
appropriate to the mode of action and to the exposure duration of the
scenario.
3.5. Extrapolation to Susceptible Populations and Lifestages
The dose-response assessment strives to derive separate estimates
for susceptible populations and lifestages so that these risks can be
explicitly characterized. For a susceptible population, higher risks
can be expected from exposures anytime during life, but this applies to
only a portion of the general population (e.g., those bearing a
particular genetic susceptibility). In contrast, for a susceptible
lifestage, higher risks can be expected from exposures during only a
portion of a lifetime, but everyone in the population may pass through
those lifestages. Effects of exposures during a susceptible period are
not equivalent to effects of exposures at other times; consequently, it
is useful to estimate the risk attributable to exposures during each
period.
Depending on the data available, a tiered approach should be used
to address susceptible populations and lifestages.
When there is an epidemiologic study or an animal bioassay
that reports quantitative results for susceptible individuals, the data
should be analyzed to provide a separate risk estimate for those who
are susceptible. If susceptibility pertains to a lifestage, it is
useful to characterize the portion of the lifetime risk that can be
attributed to the susceptible lifestage.
When there are data on some risk-related parameters that
allow comparison of the general population and susceptible individuals,
the data should be analyzed with an eye toward adjusting the general
population estimate for susceptible individuals. This analysis can
range from toxicokinetic modeling that uses parameter values
representative of susceptible individuals to more simply adjusting a
general population estimate to reflect differences in important rate-
governing parameters. Care is taken to not make parameter adjustments
in isolation, as the appropriate adjustment can depend on the
interactions of several parameters; for example, the ratio of metabolic
activation and clearance rates can be more appropriate than the
activation rate alone (U.S. EPA, 1992b).
In the absence of such agent-specific data, there is some
general information to indicate that childhood can be a susceptible
lifestage for exposure to some carcinogens (U.S. EPA, 2005); this
warrants explicit consideration in each assessment. The potential for
susceptibility from early-life exposure is expected to vary among
specific agents and chemical classes. In addition, the concern that the
dose-averaging generally used for assessing less-than-lifetime exposure
is more likely to understate than overstate risk (see Section 3.4)
contributes to the suggestion that alternative approaches be considered
for assessing risks from less-than-lifetime exposure that occurs during
childhood. Accompanying these cancer guidelines is the Supplemental
Guidance that the Agency will use to assess risks from early-life
exposure to potential carcinogens (U.S. EPA, 2005). The Supplemental
Guidance may be updated to reflect new data and new understanding that
may become available in the future.
3.6. Uncertainty
The NRC (1983, 1994, 1996, 2002) has repeatedly advised that proper
characterization of uncertainty is essential in risk assessment. An
assessment that omits or underestimates uncertainty can leave
decisionmakers with a false sense of confidence in estimates of risk.
On the other hand, a high level of uncertainty does not imply that a
risk assessment or a risk management action should be delayed (NRC,
2002). Uncertainty in dose-response assessment can be classified as
either model uncertainty or parameter uncertainty. A related concept,
human variation, is discussed below. Assessments should discuss the
significant uncertainties encountered in the analysis, distinguishing,
if possible, between model uncertainty, parameter uncertainty, and
human variation. Origins of these uncertainties can span a range, from
a single causal thread supported by sparse data, to abundant
information that presents multiple possible conclusions or that does
not coalesce. As described in Section 2.6 and in Section 5.1, all
contributing features should be noted.
Model uncertainty refers to a lack of knowledge needed to determine
which is the correct scientific theory on which to base a model. In
risk assessment, model uncertainty is reflected in alternative choices
for model structure, dose metrics, and extrapolation approaches. Other
sources of model uncertainty concern whether surrogate data are
appropriate, for example, using data on adults to make inferences about
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children. The full extent of model uncertainty usually cannot be
quantified; a partial characterization can be obtained by comparing the
results of alternative models. Model uncertainty is expressed through
comparison of separate analyses from each model, coupled with a
subjective probability statement, where feasible and appropriate, of
the likelihood that each model might be correct (NRC, 1994).
Some aspects of model uncertainty that should be addressed in an
assessment include the use of animal models as a surrogate for humans,
the influence of cross-species differences in metabolism and
physiology, the use of effects observed at high doses as an indicator
of the potential for effects at lower doses, the effect of using linear
or nonlinear extrapolation to estimate risks, the use of using small
samples and subgroups to make inferences about entire human populations
or subpopulations with differential susceptibilities, and the use of
experimental exposure regimens to make inferences about different human
exposure scenarios (NRC, 2002).
Toxicokinetic and toxicodynamic models are generally premised on
site concordance across species, modeling, for example, the
relationship between administered dose and liver tissue concentrations
to predict increased incidences of liver cancer. This relationship,
which can be observed in animals, is typically only inferred for
humans. There are, however, numerous examples of an agent causing
different cancers in different species. The assessment should discuss
the relevant data that bear on this form of model uncertainty.
Parameter uncertainty refers to a lack of knowledge about the
values of a model's parameters. This leads to a distribution of values
for each parameter. Common sources of parameter uncertainty include
random measurement errors, systematic measurement errors, use of
surrogate data instead of direct measurements, misclassification of
exposure status, random sampling errors, and use of an unrepresentative
sample. Most types of parameter uncertainty can be quantified by
statistical analysis.
Human variation refers to person-to-person differences in
biological susceptibility or in exposure. Although both human variation
and uncertainty can be characterized as ranges or distributions, they
are fundamentally different concepts. Uncertainty can be reduced by
further research that supports a model or improves a parameter
estimate, but human variation is a reality that can be better
characterized, but not reduced, by further research. Fields other than
risk assessment use ``variation'' or ``variability'' to mean dispersion
about a central value, including measurement errors and other random
errors that risk assessors address as uncertainty.
Probabilistic risk assessment, informed by expert judgment, has
been used in exposure assessment to estimate human variation and
uncertainty in lifetime average daily exposure concentration or dose.
Probabilistic methods can be used in this exposure assessment
application because the pertinent variables (for example,
concentration, intake rate, exposure duration, and body weight) have
been identified, their distributions can be observed, and the formula
for combining the variables to estimate the lifetime average daily dose
is well defined (see U.S. EPA, 1992a). Similarly, probabilistic methods
can be applied in dose-response assessment when there is an
understanding of the important parameters and their relationships, such
as identification of the key determinants of human variation (for
example, metabolic polymorphisms, hormone levels, and cell replication
rates), observation of the distributions of these variables, and valid
models for combining these variables. With appropriate data and expert
judgment, formal approaches to probabilistic risk assessment can be
applied to provide insight into the overall extent and dominant sources
of human variation and uncertainty. In doing this, it is important to
note that analyses that omit or underestimate some principal sources of
variation or uncertainty could provide a misleadingly narrow
description of the true extent of variation and uncertainty and give
decisionmakers a false sense of confidence in estimates of risk.
Specification of joint probability distributions is appropriate when
variables are not independent of each other. In each case, the
assessment should carefully consider the questions of uncertainty and
human variation and discuss the extent to which there are data to
address them.
Probabilistic risk assessment has also been used in dose-response
assessment to determine and distinguish the degree of uncertainty and
variability in toxicokinetic and toxicodynamic modeling. Although this
field is less advanced that probabilistic exposure assessment, progress
is being made and these cancer guidelines are flexible enough to
accommodate continuing advances in these approaches.
Advances in uncertainty analysis are expected as the field
develops. The cancer guidelines are intended to be flexible enough to
incorporate additional approaches for characterizing uncertainty that
have less commonly been used by regulatory agencies. In all scientific
and engineering fields, data and research limitations often limit the
application of established methods. A dearth of data is a particular
problem when quantifying the probability distribution of model outputs.
In many of these scientific and engineering disciplines, researchers
have used rigorous expert elicitation methods to overcome the lack of
peer-reviewed methods and data. Although expert elicitation has not
been widely used in environmental risk assessment, several studies have
applied this methodology as a tool for understanding quantitative risk.
For example, expert elicitation has been used in chemical risk
assessment and its associated uncertainty (e.g., Richmond, 1981; Renn,
1999; Florig et al., 2001; Morgan et al., 2001; Willis et al., 2004),
components of risk assessment such as hazard assessment and dose-
response evaluation (e.g., Hawkins and Graham 1988; Jelovsek et al.,
1990; Evans et al., 1994; IEc, 2004; U.S. EPA 2004) and exposure
assessment (e.g., Whitfield and Wallsten, 1989; Hawkins and Evans,
1989; Winkler et al., 1995; Stiber et al., 1999; Walker et al., 2001,
2003; Van Der Fels-Klerx et al., 2002), and for evaluating other types
of risks (e.g., North and Merkhofer, 1976; Fos and McLin, 1990). These
cancer guidelines are flexible enough to accommodate the use of expert
elicitation to characterize cancer risks, as a complement to the
methods presented in the cancer guidelines. According to NRC (NRC,
2002), the rigorous use of expert elicitation for the analyses of risks
is considered to be quality science.
3.7. Dose-Response Characterization
A dose-response characterization extracts the dose-response
information needed in a full risk characterization (U.S. EPA, 2000b),
including:
Presentation of the recommended estimates (slope factors,
reference doses, reference concentrations) and alternatives with
significant biological support,
A summary of the data supporting these estimates,
A summary and explanation of the modeling approaches used,
A description of any special features such as the
development and consolidation of multiple estimates as detailed in
Section 3.3.5,
The POD narrative (see Section 3.2.5),
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A summary of the key defaults invoked,
Identification of susceptible populations or lifestages
and quantification of their differential susceptibility, and
A discussion of the strengths and limitations of the dose-
response assessment, highlighting significant issues in developing risk
estimates, alternative approaches considered equally plausible, and how
these issues were resolved.
All estimates should be accompanied by the weight of evidence
descriptor and its narrative (see Section 2.5) to convey a sense of the
qualitative uncertainty about whether the agent may or may not be
carcinogenic.
Slope factors generally represent an upper bound on the average
risk in a population or the risk for a randomly selected individual but
not the risk for a highly susceptible individual or group. Some
individuals face a higher risk and some face a lower risk. The use of
upper bounds generally is considered to be a health-protective approach
for covering the risk to susceptible individuals, although the
calculation of upper bounds is not based on susceptibility data.
Similarly, exposure during some lifestages can contribute more or less
to the total lifetime risk than do similar exposures at other times.
The dose-response assessment characterizes, to the extent possible, the
extent of these variations.
Depending on the supporting data and modeling approach, a slope
factor can have a mix of traits that tend to either estimate,
overestimate, or underestimate risk.
Some examples of traits that tend to overestimate risk include the
following.
The slope factor is derived from data on a highly
susceptible animal strain.
Linear extrapolation is used as a default and extends over
several orders of magnitude.
The largest of several slope factors is chosen.
Some examples of traits that tend to underestimate risk include the
following.
Several tumor types were observed, but the slope factor is
based on a subset of them.
The study design does not include exposure during a
susceptible lifestage, for example, perinatal exposure.
The study population is of less-than-average
susceptibility, for example, healthy adult workers.
There is random exposure misclassification or random
exposure measurement error in the study from which the slope factor is
derived.
Some examples of traits that inherently neither overestimate nor
underestimate risk include the following.
The slope factor is derived from data in humans or in an
animal strain that responds like humans.
Linear extrapolation is appropriate for the agent's mode
of action.
Environmental exposures are close to the observed data.
Several slope factors for the same tumor are averaged or a
slope factor is derived from pooled data from several studies.
The slope factor is derived from the only suitable study.
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4. Exposure Assessment
Exposure assessment is the determination (qualitative and
quantitative) of the magnitude, frequency, and duration of exposure and
internal dose (U.S. EPA, 1992a). This section provides a brief overview
of exposure assessment principles, with an emphasis on issues related
to carcinogenic risk assessment. The information presented here should
be used in conjunction with other guidance documents, including
Guidelines for Exposure Assessment (U.S. EPA, 1992a), Science Policy
Council Handbook: Risk Characterization (U.S. EPA, 2000b), Exposure
Factors Handbook (U.S. EPA, 1997c), the 1997 Policy for Use of
Probabilistic Analysis in Risk Assessments (U.S. EPA, 1997d), and the
1997 Guiding Principles for Monte Carlo Analysis (U.S. EPA, 1997e). In
addition, program-specific guidelines for exposure assessment should be
consulted.
Exposure assessment generally consists of four major steps:
defining the assessment questions, selecting or developing the
conceptual and mathematical models, collecting data or selecting and
evaluating available data, and exposure characterization. Each of these
steps is briefly described below.
4.1. Defining the Assessment Questions
In providing a clear and unambiguous statement of the purpose and
scope of the exposure assessment (U.S. EPA, 1997e), consider the
following.
The management objectives of the assessment will determine
whether deterministic screening level analyses are adequate or whether
full probabilistic exposure characterization is needed.
Identify and include all important sources (e.g.,
pesticide applications), pathways (e.g., food or water), and routes
(e.g., ingestion, inhalation, and dermal) of exposure in the
assessment. If a particular source, pathway, or route is omitted, a
clear and transparent explanation should be provided.
Separate analyses should be conducted for each definable
subgroup within the population of interest. In particular,
subpopulations or lifestages that are believed to be highly exposed or
susceptible to a particular health effect should be studied. These
include people with certain diseases or genetic susceptibilities and
others whose behavior or physiology may lead to higher exposure or
susceptibility. Consider the following examples:
--Physiological differences between men and women (e.g., body weight
and inhalation rate) may lead to important differences in exposures.
See, for example, the discussion in Exposure Factors Handbook (U.S.
EPA, 1997c, Appendix 1A).
--Pregnant and lactating women may have exposures that differ from the
general population (e.g., slightly higher water consumption) (U.S. EPA,
1997c). Further, exposure to pregnant women may result in exposure to
the developing fetus (NRC, 1993b).
--Children consume more food per body weight than do adults while
consuming fewer types of foods, i.e., have a more limited diet (ILSI,
1992; NRC, 1993b; U.S. EPA, 1997c). In addition, children engage in
crawling and mouthing (i.e., putting hands and objects in the mouth)
behaviors, which can increase their exposures.
--The elderly and disabled may have important differences in their
exposures due to a more sedentary lifestyle (U.S. EPA, 1997c). In
addition, the health status of this group may affect their
susceptibility to the detrimental effects of exposure.
For further guidance, see Guidelines for Exposure Assessment (U.S.
EPA, 1992a, Sec. 3).
4.2. Selecting or Developing the Conceptual and Mathematical Models
Carcinogen risk assessment models have generally been based on the
premise that risk is proportional to cumulative lifetime dose. For
lifetime human exposure scenarios, therefore, the exposure metric used
for carcinogenic risk assessment has been the lifetime average daily
dose (LADD) or, in the case of inhalation exposure, the lifetime
average exposure concentration. These metrics are typically used in
conjunction with the corresponding slope factor to calculate individual
excess cancer risk. The LADD is typically an estimate of the daily
intake of a carcinogenic agent throughout the entire life of an
individual, while the lifetime average exposure concentration is the
corresponding estimate of average exposure concentration for the
carcinogenic agent over the entire life of an individual. Depending on
the objectives of the assessment, the LADD or lifetime average exposure
concentration may be calculated deterministically (using point
estimates for each factor to derive a point estimate of the exposure)
or stochastically (using probability distributions to represent each
factor and such techniques as Monte Carlo analysis to derive a
distribution of the LADD) (U.S. EPA, 1997e). Stochastic analyses may
help to identify certain population segments or lifestages that are
highly exposed and may need to be assessed as a special subgroup. For
further guidance, see Guidelines for Exposure Assessment (U.S. EPA,
1992a, Sec. 5.3.5.2 ). As methodological research focuses on new
approaches for estimating risks from less-than-lifetime exposures,
methods and defaults can be expected to change.
There may be cases where the mode of action indicates that dose
rates are important in the carcinogenic process. In these cases, short-
term, less-than-lifetime exposure estimates may be more appropriate
than the LADD for risk assessment. This may be the case when a
nonlinear dose-response approach is used (see Section 3.3.4).
4.3. Collecting Data or Selecting and Evaluating Available Data
After the assessment questions have been defined and the conceptual
and mathematical models have been developed, it is important to compile
and evaluate existing data or, if necessary, to collect new data.
Depending on the exposure scenario under consideration, data on a wide
variety of exposure factors may be needed. EPA's Exposure Factors
Handbook (U.S. EPA, 1997c) contains a large compilation of exposure
data, with some analysis and recommendations. Some of these data are
organized by age groups to assist with assessing such subgroups as
children. See, for example, Exposure Factors Handbook (U.S. EPA, 1997c,
Volume 1, Chapter 3). When using these existing data, it is important
to evaluate the quality of the data and the extent to which the data
are representative of the population under consideration. EPA's (U.S.
EPA, 2000d) and OMB's (OMB 2002) guidance on information quality, as
well as program-specific guidances can provide further assistance for
evaluating existing data.
When existing data fail to provide an adequate surrogate for the
needs of a particular assessment, it is important to collect new data.
Such data collection efforts should be guided by the references listed
above (e.g., Guidance for Data Quality Assessment and program-specific
guidance). Once again, subpopulations or lifestages of concern are an
important consideration in any data collection effort.
4.3.1. Adjusting Unit Risks for Highly Exposed Populations and
Lifestages
Unit risk estimates that have been developed in the dose-response
assessment often assumed standard adult intake rates. When an exposure
assessment focuses on a population or lifestage with differential
exposure, good exposure assessment practice would replace the standard
intake rates
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with values representative of the exposed population. Small changes in
exposure assessments can be approximated by using linearly proportional
adjustments of exposure parameters, but a more accurate integrative
analysis may require an analysis stratified by exposure duration (see
Section 5.1).
For example, to adjust the drinking water unit risk for an
active population that drinks 4 L/day (instead of 2 L/day), multiply
the unit risk by 2.
Because children drink more water relative to their body weight
than do adults (U.S. EPA, 2002d), adjustments to unit risk estimates
are warranted whenever they are applied in an assessment of childhood
exposure.
For example, to adjust the drinking water unit risk for a 9-kg
infant who drinks 1 L/day (instead of a 70-kg adult who drinks 2 L/
day), multiply the unit risk by [(1 L/day) / (9 kg)] / [(2 L/day) /
(70 kg)] = 3.9.
Inhalation dosimetry is employed to derive the human equivalent
exposure concentrations on which inhalation unit risks, and reference
concentrations, are based (U.S. EPA, 1994). As described previously
(see Sections 3.1.2, 3.1.3), different dosimetry methods may be
employed depending on the availability of relevant data and chemical-
specific characteristics of the pollutant. Consideration of lifestage-
particular physiological characteristics in the dosimetry analysis may
result in a refinement to the human equivalent concentration (HEC) to
insure relevance in risk assessment across lifestages, or might
conceivably conclude with multiple HECs, and corresponding inhalation
unit risk values (e.g., separate for childhood and adulthood).
The dose-response assessment discusses the key sources of
uncertainty in estimating dosimetry, including any related to
lifestage. Review of this discussion and of the dosimetric analysis
performed in deriving the HEC and resultant unit risk will assist in
the appropriate application of inhalation unit risk values to exposure
across lifestages.
4.4. Exposure Characterization
The exposure characterization is a technical characterization that
presents the assessment results and supports the risk characterization.
It provides a statement of the purpose, scope, and approach used in the
assessment, identifying the exposure scenarios and population subgroups
covered. It provides estimates of the magnitude, frequency, duration,
and distribution of exposures among members of the exposed population
as the data permit. It identifies and compares the contribution of
different sources, pathways, and routes of exposure. In particular, a
qualitative discussion of the strengths and limitations (uncertainties)
of the data and models are presented.
The discussion of uncertainties is a critical component of the
exposure characterization. Uncertainties can arise out of problems with
the conceptual and mathematical models. Uncertainties can also arise
from poor data quality and data that are not quite representative of
the population or scenario of interest. Consider the following examples
of uncertainties.
National data (i.e., data collected to represent the
entire U.S. population) may not be representative of exposures
occurring within a regional or local population.
Use of short-term data to infer chronic, lifetime
exposures should be done with caution. Use of short-term data to
estimate long-term exposures has the tendency to underestimate the
number of people exposed while overestimating the exposure levels
experienced by those in the upper end (i.e., above the 90th percentile)
of the exposure distribution. For further guidance, refer to Guidelines
for Exposure Assessment (U.S. EPA, 1992a, Sec. 5.3.1).
Children's behavior, including their more limited diet,
may lead to relatively high but intermittent exposures. This pattern of
exposure, ``one that gradually declines over the developmental period
and which remains relatively constant thereafter'' is not accounted for
in the LADD model (ILSI, 1992). Further, the physiological
characteristics of children may lead to important differences in
exposure. Some of these differences can be accounted for in the LADD
model. For further guidance, see Guidelines for Exposure Assessment
(U.S. EPA, 1992a, Sec. 5.3.5.2).
Overall, the exposure characterization should provide a full
description of the sources, pathways, and routes of exposure. The
characterization also should include a full description of the
populations assessed. In particular, highly exposed or susceptible
subpopulation or lifestage should be discussed. For further guidance on
the exposure characterization, consult Guidelines for Exposure
Assessment (U.S. EPA, 1992a), the Policy and Guidance for Risk
Characterization (U.S. EPA, 2000b,1995) and EPA's Rule Writer's Guide
to Executive Order 13045 (especially Attachment C: Technical Support
for Risk Assessors--Suggestions for Characterizing Risks to Children
[U.S. EPA, 1998d]).
5. Risk Characterization
5.1. Purpose
EPA has developed general guidance on risk characterization for use
in its risk assessment activities. The core of EPA's risk
characterization policy (U.S. EPA, 2000b, 1995) includes the following.
Each risk assessment prepared in support of decision making at
EPA should include a risk characterization that follows the
principles and reflects the values outlined in this policy. A risk
characterization should be prepared in a manner that is clear,
transparent, reasonable, and consistent with other risk
characterizations of similar scope prepared across programs in the
Agency. Further, discussion of risk in all EPA reports,
presentations, decision packages, and other documents should be
substantively consistent with the risk characterization. The nature
of the risk characterization will depend upon the information
available, the regulatory application of the risk information, and
the resources (including time) available. In all cases, however, the
assessment should identify and discuss all the major issues
associated with determining the nature and extent of the risk and
provide commentary on any constraints limiting fuller exposition.
Risk characterization should be carried out in accordance with the
EPA (U.S. EPA, 2002a) and OMB (2002) information quality guidelines.
EPA's risk characterization handbook (U.S. EPA, 2000b) provides
detailed guidance to Agency staff. The discussion below does not
attempt to duplicate this material, but it summarizes its applicability
to carcinogen risk assessment.
The risk characterization includes a summary for the risk manager
in a nontechnical discussion that minimizes the use of technical terms.
It is an appraisal of the science that informs the risk manager in
public health decisions, as do other decision-making analyses of
economic, social, or technology issues. It also serves the needs of
other interested readers. The summary is an information resource for
preparing risk communication information, but being somewhat more
technical than desired for communication with the general public, is
not itself the usual vehicle for communication with every audience.
The risk characterization also brings together the assessments of
hazard, dose response, and exposure to make risk estimates for the
exposure scenarios of interest. This analysis that follows the summary
is generally much more extensive. It typically will identify exposure
scenarios of interest in decision making and present risk analyses
associated with them. Some of the analyses may concern scenarios in
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several media; others may examine, for example, only drinking water
risks. As these cancer guidelines allow different hazard
characterizations and different potencies for specified conditions,
e.g., exposure level, route of exposure, or lifestage, some of the
integrative analyses may need to be stratified to accommodate the
appropriate combinations of parameters across relevant exposure
durations.
In constructing high end estimates of risk, the assessor should
bear in mind that the high-end risk is a plausible estimate of the risk
for those persons at the upper end of the risk distribution (U.S. EPA,
1992a). The intent of this approach is to convey an estimate of risk in
the upper range of the distribution, but to avoid estimates that are
beyond the true distribution. Overly conservative assumptions, when
combined, can lead to unrealistic estimates of risk. This means that
when constructing estimates from a series of factors (e.g., emissions,
exposure, and unit risk estimates) not all factors should be set to
values that maximize exposure, dose, or effect, since this will almost
always lead to an estimate that is above the 99th-percentile confidence
level and may be of limited use to decisionmakers. This is particularly
problematic when using unbounded lognormal factor distributions.
While it is an appropriate aim to assure protection of health and
the environment in the face of scientific uncertainty, common sense,
reasonable applications of assumptions and policy, and transparency are
essential to avoid unrealistically high estimates. It is also important
to inform risk managers of the final distribution of risk estimates
(U.S. EPA, 2000b; 1995). Otherwise, risk management decisions may be
made on varying levels of conservatism, leading to misplaced risk
priorities and potentially higher overall risks. (Nichols and
Zeckhauser,1986; Zeckhauser and Viscusi,1990).
The risk characterization presents an integrated and balanced
picture of the analysis of the hazard, dose-response, and exposure. The
risk analyst should provide summaries of the evidence and results and
describe the quality of available data and the degree of confidence to
be placed in the risk estimates. Important features include the
constraints of available data and the state of knowledge, significant
scientific issues, and significant science and science policy choices
that were made when alternative interpretations of data exist (U.S.
EPA, 1995, 2000b). Choices made about using data or default options in
the assessment are explicitly discussed in the course of analysis, and
if a choice is a significant issue, it is highlighted in the summary.
In situations where there are alternative approaches for a risk
assessment that have significant biological support, the decisionmaker
can be informed by the presentation of these alternatives along with
their strengths and uncertainties.
5.2. Application
Risk characterization is a necessary part of generating any Agency
report on risk, whether the report is preliminary--to support
allocation of resources toward further study--or comprehensive--to
support regulatory decisions. In the former case, the detail and
sophistication of the characterization are appropriately small in
scale; in the latter case, appropriately extensive. Even if a document
covers only parts of a risk assessment (hazard and dose-response
analyses, for instance), the results of these are characterized.
Risk assessment is an iterative process that grows in depth and
scope in stages from screening for priority making to preliminary
estimation to fuller examination in support of complex regulatory
decision making. Default options may be used at any stage, but they are
predominant at screening stages and are used less as more data are
gathered and incorporated at later stages. Various provisions in EPA-
administered statutes require decisions based on differing findings for
which differing degrees of analysis are appropriate. There are close to
30 provisions within the major statutes that require decisions based on
risk, hazard, or exposure assessment. For example, Agency review of
pre-manufacture notices under Section 5 of the Toxic Substances Control
Act relies on screening analyses, whereas requirements for industry
testing under Section 4 of that Act rely on preliminary analyses of
risk or simply of exposure. In comparison, air quality criteria under
the Clean Air Act rest on a rich data collection and are required by
statute to undergo periodic reassessment. There are provisions that
require ranking of hazards of numerous pollutants--which may be
addressed through a screening level of analysis--and other provisions
for which a full assessment of risk is more appropriate.
Given this range in the scope and depth of analyses, not all risk
characterizations can or should be equal in coverage or depth. The risk
assessor should carefully decide which issues in a particular
assessment are important to present, choosing those that are noteworthy
in their impact on results. For example, health effect assessments
typically rely on animal data because human data are rarely available.
The objective of characterization of the use of animal data is not to
recount generic issues about interpreting and using animal data; Agency
guidance documents cover these issues. Rather, the objective is to
highlight any significant issues that arose within the particular
assessment being characterized and inform the reader about significant
uncertainties that affect conclusions.
5.3. Presentation of the Risk Characterization Summary
The presentation is a nontechnical discussion of important
conclusions, issues, and uncertainties that uses the hazard, dose
response, exposure, and integrative analyses for technical support. The
primary technical supports within the risk assessment are the hazard
characterization, dose-response characterization, and exposure
characterization described in these cancer guidelines. The risk
characterization is derived from these. The presentation should fulfill
the aims outlined in the purpose section above.
5.4. Content of the Risk Characterization Summary
Specific guidance on hazard, dose-response, and exposure
characterization appears in previous sections. Overall, the risk
characterization routinely includes the following, capturing the
important items covered in hazard, dose response, and exposure
characterization:
Primary conclusions about hazard, dose response, and
exposure, including alternatives with significant biological support;
Nature of key supporting information and analytic methods;
Risk estimates and their attendant uncertainties,
including key uses of default options when data are missing or
uncertain.
--With linear extrapolations, risk below the POD is typically
approximated by multiplying the slope factor by an estimate of
exposure, i.e., Risk = Slope Factor x Exposure. For exposure levels
above the POD, the dose-response model is used instead of this
approximation.
--With nonlinear extrapolations, the method of risk assessment depends
on the procedure used. If a nonlinear dose-response function has been
determined, it can be used with the expected exposure to estimate a
risk. If an RfD or RfC was calculated, the hazard can be expressed as a
hazard quotient (HQ), defined as the ratio of an exposure estimate over
the
[[Page 17809]]
reference dose (RfD) or reference concentration (RfC), i.e., HQ =
Exposure / (RfD or RfC). From the hazard quotient, it can generally be
inferred whether the nonlinear mode of action is relevant at the
environmental exposure level in question;
Statement of the extent of extrapolation of risk estimates
from observed data to exposure levels of interest and its implications
for certainty or uncertainty in quantifying risk. The extent of
extrapolation can be expressed as a margin of exposure (MOE), defined
as the ratio of the POD over an exposure estimate (MOE = POD /
Exposure);
Significant strengths and limitations of the data and
analyses, including any major peer review issues;
Appropriate comparison with similar EPA risk analyses or
common risks with which people may be familiar; and
Comparison with all appropriate assessments of the same
problem by others.
It is often difficult to know a priori when or how different
results of a cancer risk assessment are likely to be used by Agency
economists, policy analysts, and decisionmakers, so it is important
that the resulting characterizations include the necessary information
for these analyses to the extent practicable. OMB and EPA guidelines
for benefit-cost analysis require expected or central estimates of risk
and information on the uncertainty of the estimate when it is possible
or practicable. The extent of the uncertainty information needed for
analysis depends, in part, on the scale of the policy being considered,
with formal quantitative analysis of uncertainty being required in some
cases.\6\ OMB Circular A-4 (OMB, 2003) emphasizes that agencies
``should try to provide some estimate of the probability distribution
of regulatory benefits and costs.'' These OMB guidelines note,
``Whenever it is possible to characterize quantitatively the
probability distribution, some estimates of expected value * * * must
be provided in addition to ranges, variances, specified low-end and
high-end percentile estimates, and other characteristics of the
distribution.'' The risk characterization should therefore include,
where practicable, expected or central estimates of risk, as well as
upper and lower bounds, e.g., confidence limits, based on the POD, if
not a full characterization of uncertainty of the risk. As discussed in
EPA's Guidelines for Ensuring and Maximizing the Quality, Objectivity,
Utility, and Integrity of Information Disseminated by the Environmental
Protection Agency (Appendix B), statutory mandates, such as the Safe
Drinking Water Act, the Food Quality Protection Act, and the Clean Air
Act, call for the Agency to generate specific kinds of risk
information, and thus these updated cancer assessment guidelines should
be read in conjunction with the Agency's statutory mandates regarding
risk assessment.
---------------------------------------------------------------------------
\6\ Specifically, OMB guidelines state: ``For rules that exceed
the $1 billion annual [economic effects] threshold, a formal
quantitative analysis of uncertainty is required. For rules with
annual benefits and/or costs in the range from 100 million to $1
billion, you should seek to use more rigorous approaches with higher
consequence rules.'' (OMB, 2003, page 158)
---------------------------------------------------------------------------
Appendix A: Major Default Options
This discussion covers the major default options commonly employed
when data are missing or sufficiently uncertain in a cancer risk
assessment, as adopted in these cancer guidelines. These options are
predominantly inferences that help use the data observed under
empirical conditions in order to estimate events and outcomes under
environmental conditions. Several inferential issues arise when effects
seen in a subpopulation of humans or animals are used to infer
potential effects in the population of environmentally exposed humans.
Several more inferential issues arise in extrapolating the exposure-
effect relationship observed empirically to lower-exposure
environmental conditions. The following issues cover the major default
areas.
Is the presence or absence of effects observed in a human
population predictive of effects in another exposed human population?
Is the presence or absence of effects observed in an
animal population predictive of effects in exposed humans?
How do metabolic pathways relate across species and among
different age groups and between sexes in humans?
How do toxicokinetic processes relate across species and
among different age groups and between sexes in humans?
What is the relationship between the observed dose-
response relationship to the relationship at lower doses?
Is the Presence or Absence of Effects Observed in a Human Population
Predictive of Effects in Another Exposed Human Population?
When cancer effects in exposed humans are attributed to exposure to
an agent, the default option is that the resulting data are predictive
of cancer in any other exposed human population. Most studies
investigating cancer outcomes in humans from exposure to agents are
often studies of occupationally exposed humans. By sex, age, and
general health, workers may not be representative of the general
population exposed environmentally to the same agents. In such studies
there is no opportunity to observe subpopulations who are likely to be
under represented, such as fetuses, infants and children, women, or
people in poor health, who may respond differently from healthy
workers. Therefore, it is understood that this option could still
underestimate the response of certain human subpopulations (NRC, 1993b,
1994).
When cancer effects are not found in an exposed human population,
this information by itself is not generally sufficient to conclude that
the agent poses no carcinogenic hazard to this or other populations of
potentially exposed humans, including susceptible subpopulations or
lifestages. This is because epidemiologic studies often have low power
to detect and attribute responses and typically evaluate cancer
potential in a restricted population (e.g., by age, healthy workers).
The topic of susceptibility and variation is addressed further in the
discussion below of quantitative default options about dose-response
relationships. Well-conducted studies that fail to detect a
statistically significant positive association, however, may have value
and should be judged on their merits, including population size,
duration of the study, the quality of the exposure characterization and
measures of outcome, and the magnitude and duration of the exposure.
There is not yet enough knowledge to form a basis for any generally
applicable qualitative or quantitative inference to compensate for the
gap in knowledge concerning other populations. In these cancer
guidelines, this problem is left to analysis in individual cases, to be
attended to with further general guidance as future research and
information allow. When information on a susceptible subpopulation or
lifestage exists, it will be used. For example, an agent such as
diethylstilbestrol (DES) causes a rare form of vaginal cancer (clear-
cell adenocarcinoma) (Herbst et al., 1971) in about 1 per 1000 of adult
women whose mothers were exposed during pregnancy (Hatch et al., 1998).
[[Page 17810]]
Is the Presence or Absence of Effects Observed in an Animal Population
Predictive of Effects in Exposed Humans?
The default option is that positive effects in animal cancer
studies indicate that the agent under study can have carcinogenic
potential in humans. Thus, if no adequate human or mode of action data
are present, positive effects in animal cancer studies are a basis for
assessing the carcinogenic hazard to humans. This option is a public
health-protective policy, and it is both appropriate and necessary,
given that we do not test for carcinogenicity in humans. The option is
supported by the fact that nearly all of the agents known to cause
cancer in humans are carcinogenic in animals in tests that have
adequate protocols (IARC, 1994; Tomatis et al., 1989; Huff, 1994).
Moreover, almost one-third of human carcinogens were identified
subsequent to animal testing (Huff, 1993). Further support is provided
by research on the molecular biology of cancer processes, which has
shown that the mechanisms of control of cell growth and differentiation
are remarkably homologous among species and highly conserved in
evolution. Nevertheless, the same research tools that have enabled
recognition of the nature and commonality of cancer processes at the
molecular level also have the power to reveal differences and instances
in which animal responses are not relevant to humans (Lijinsky, 1993;
U.S. EPA, 1991b). Under these cancer guidelines, available mode of
action information is studied for its implications in both hazard and
dose-response assessment and its ability to obviate default options.
There may be instances in which the use of an animal model would
identify a hazard in animals that is not truly a hazard in humans
(e.g., the alpha-2u-globulin association with renal neoplasia in male
rats [U.S. EPA, 1991b]). The extent to which animal studies may yield
false positive indications for humans is a matter of scientific debate.
To demonstrate that a response in animals is not relevant to any human
situation, adequate data to assess the relevancy issue are important.
In general, while effects seen at the highest dose tested are
assumed to be appropriate for assessment, it is necessary that the
experimental conditions be scrutinized. Animal studies are conducted at
high doses in order to provide statistical power, the highest dose
being one that is minimally toxic (maximum tolerated dose or MTD).
Consequently, the question often arises of whether a carcinogenic
effect at the highest dose may be a consequence of cell killing with
compensatory cell replication or of general physiological disruption
rather than inherent carcinogenicity of the tested agent. There is
little doubt that this may happen in some cases, but skepticism exists
among some scientists that it is a pervasive problem (Ames and Gold,
1990; Melnick et al., 1993; Barrett, 1993). If adequate data
demonstrate that the effects are solely the result of excessive
toxicity rather than carcinogenicity of the tested agent per se, then
the effects may be regarded as not appropriate to include in assessment
of the potential for human carcinogenicity of the agent. This is a
matter of expert judgment, with consideration given to all of the data
available about the agent, including effects in other toxicity studies,
structure-activity relationships, and effects on growth control and
differentiation.
When cancer effects are not found in well-conducted animal cancer
studies in two or more appropriate species and other information does
not support the carcinogenic potential of the agent, these data provide
a basis for concluding that the agent is not likely to possess human
carcinogenic potential, in the absence of human data to the contrary.
This default option about lack of cancer effects has limitations. It is
recognized that animal studies (and epidemiologic studies as well) have
very low power to detect cancer effects. Detection of a 10% tumor
incidence is generally the limit of power with standard protocols for
animal studies (with the exception of rare tumors that are virtually
markers for a particular agent, e.g., angiosarcoma caused by vinyl
chloride). In some situations, the tested animal species may not be
predictive of effects in humans; for example, arsenic shows only
minimal or no effect in animals, whereas it is clearly positive in
humans. Therefore, it is important to consider other information as
well; absence of mutagenic activity or absence of carcinogenic activity
among structural analogues can increase the confidence that negative
results in animal studies indicate a lack of human hazard.
Another limitation is that standard animal study protocols are not
yet available for effectively studying perinatal effects. The potential
for effects on the very young generally should be considered
separately. Under existing Agency policy (U.S. EPA, 1997a, b),
perinatal studies accomplished by modification of existing adult
bioassay protocols are important in special circumstances.
Target organ concordance is not a prerequisite for evaluating the
implications of animal study results for humans. Target organs of
carcinogenesis for agents that cause cancer in both animals and humans
are most often concordant at one or more sites (Tomatis et al., 1989;
Huff, 1994). However, concordance by site is not uniform. The
mechanisms of control of cell growth and differentiation are concordant
among species, but there are marked differences among species in the
way control is managed in various tissues. For example, in humans,
mutations of the tumor suppressor genes p53 and retinoblastoma are
frequently observed genetic changes in tumors. These tumor-suppressor
genes are also observed to be operating in some rodent tissues, but
other growth control mechanisms predominate in other rodent tissues.
Thus, an animal response may be due to changes in a control that are
relevant to humans but appear in animals in a different way.
However, it is appropriate under these cancer guidelines to
consider the influences of route of exposure, metabolism, and,
particularly, some modes of action that may either support or not
support target organ concordance between animals and humans. When data
allow, these influences are considered in deciding whether agent-,
species-, or organ-specific situations are appropriate to use in
preference to this default assumption (NRC, 1994). In contrast, use of
toxicokinetic modeling inherently assumes site concordance, as these
models are used to estimate delivered dose to a particular tissue or
organ in humans on the basis of the same tissue or organ from animal
data.
The default is to include benign tumors observed in animal studies
in the assessment of animal tumor incidence, if such tumors have the
capacity to progress to the malignancies with which they are
associated. This default is consistent with the approach of the
National Toxicology Program and the International Agency for Research
on Cancer and is more protective of public health than not including
benign tumors in the assessment; benign and malignant tumors are
treated as representative of related responses to the test agent
(McConnell et al., 1986), which is scientifically appropriate.
Nonetheless, in assessing findings from animal studies, a greater
proportion of malignancy is weighed more heavily than is a response
with a greater proportion of benign tumors. Greater frequency of
malignancy of a particular tumor type in comparison with other tumor
responses observed in an animal study is also a factor to be considered
[[Page 17811]]
in selecting the response to be used in dose-response assessment.
Benign tumors that are not observed to progress to malignancy are
assessed on a case-by-case basis. There is a range of possibilities for
the overall significance of benign tumors. They may deserve attention
because they are serious health problems even though they are not
malignant; for instance, benign tumors may be a health risk because of
their effect on the function of a target tissue, such as the brain.
They may be significant indicators of the need for further testing of
an agent if they are observed in a short-term test protocol, or such an
observation may add to the overall weight of evidence if the same agent
causes malignancies in a long-term study. Knowledge of the mode of
action associated with a benign tumor response may aid in the
interpretation of other tumor responses associated with the same agent.
How Do Metabolic Pathways Relate Across Species and Among Different Age
Groups and Between Sexes in Humans?
The default option is that there is a similarity of the basic
pathways of metabolism and the occurrence of metabolites in tissues in
regard to the species-to-species extrapolation of cancer hazard and
risk. If comparative metabolism studies were to show no similarity
between the tested species and humans and a metabolite(s) was the
active form, there would be less support for an inference that the
animal response(s) relates to humans. In other cases, parameters of
metabolism may vary quantitatively between species; this becomes a
factor in deciding on an appropriate human-equivalent dose based on
animal studies, optimally in the context of a toxicokinetic model.
Although the basic pathways are assumed to be the same among humans,
the presence of polymorphisms in the general population and factors
such as the maturation of the pathways in infants should be considered.
The active form of an agent may be present to differing degrees, or it
may be completely absent, which may result in greater or lesser risk
for subpopulations.
How Do Toxicokinetic Processes Relate Across Species and Among
Different Age Groups and Between Sexes in Humans?
A major issue is how to estimate human-equivalent doses in
extrapolating from animal studies. As a default for oral exposure, a
human equivalent dose for adults is estimated from data on another
species by an adjustment of animal applied oral dose by a scaling
factor based on body weight to the \3/4\ power. The same factor is used
for children because it is slightly more protective than using
children's body weight (see Section 3.1.3). This adjustment factor is
used because it represents scaling of metabolic rate across animals of
different size. Because the factor adjusts for a parameter that can be
improved on and brought into more sophisticated toxicokinetic modeling
when such data become available, they are usually preferable to the
default option.
For inhalation exposure, a human equivalent dose for adults is
estimated by default methodologies that provide estimates of lung
deposition and internal dose (U.S. EPA, 1994). The methodologies can be
refined to more sophisticated forms with data on toxicokinetic and
metabolic parameters of the specific agent. This default option, like
the one for oral exposure, is selected in part because it lays a
foundation for incorporating better data. The use of information to
improve dose estimation from applied to internal to delivered dose is
encouraged, including use of toxicokinetic modeling instead of any
default, where data are available.
There are important differences between infants, adults, and older
adults in the processes of absorption, distribution, and elimination;
for example, infants tend to absorb metals through the gut more rapidly
and more efficiently than do older children or adults (Calabrese,
1986). Renal elimination is also not as efficient in infants. Although
these processes reach adult competency at about the time of weaning,
they may have important implications, particularly when the dose-
response relationship for an agent is considered to be nonlinear and
there is an exposure scenario disproportionately affecting infants,
because in these cases the magnitude of dose is more pertinent than the
usual approach in linear extrapolation of averaging dose across a
lifetime. Efficiency of intestinal absorption in older adults tends to
be generally less overall for most chemicals. Another notable
difference is that, post-weaning (about 1 year), children have a higher
metabolic rate than do adults (Renwick, 1998), and they may toxify or
detoxify agents at a correspondingly higher rate.
For a route-to-route exposure extrapolation, the default option is
that an agent that causes internal tumors by one route of exposure will
be carcinogenic by another route if it is absorbed by the second route
to give an internal dose. This is a qualitative option and is
considered to be public-health protective. The rationale is that for
internal tumors an internal dose is significant no matter what the
route of exposure. Additionally, the metabolism of the agent will be
qualitatively the same for an internal dose. The issue of quantitative
extrapolation of the dose-response relationship from one route to
another is addressed case by case. Quantitative extrapolation is
complicated by considerations such as first-pass metabolism.
What Is the Correlation of the Observed Dose-Response Relationship to
the Relationship at Lower Doses?
If sufficient data are available, a biologically based model for
both the observed range and extrapolation below that range may be used.
Although no standard biologically based models are in existence, an
agent-specific model may be developed if extensive data exist in a
particular case and the purpose of the assessment justifies the
investment of the resources needed. The default procedure for the
observed range of data when a biologically based model is not used is
to use a curve-fitting model for incidence data.
In the absence of data supporting a biologically based model for
extrapolation outside of the observed range, the choice of approach is
based on the view of mode of action of the agent arrived at in the
hazard assessment. If more than one approach (e.g., both a nonlinear
and linear approach) are supported by the data, they should be used and
presented to the decisionmaker.
A linear extrapolation approach is used when the mode of action
information is supportive of linearity or mode of action is not
understood. The linear approach is used when a view of the mode of
action indicates a linear response, for example, when a conclusion is
made that an agent directly causes alterations in DNA, a kind of
interaction that not only theoretically requires one reaction but also
is likely to be additive to ongoing, spontaneous gene mutation. Other
kinds of activity may have linear implications, for example, linear
rate-limiting steps would also support a linear procedure. The linear
approach is to draw a straight line between a point of departure from
observed data, generally as a default, an LED chosen to be
representative of the lower end of the observed range, and the origin
(zero incremental dose, zero incremental response). This approach is
generally considered to be public-health protective.
The linear default is thought to generally provide an upper-bound
calculation of potential risk at low doses, for example, a
[[Page 17812]]
1/100,000 to 1/1,000,000 risk. This upper bound is thought to be
public-health protective at low doses for the range of human variation,
considering the typical Agency target range for risk management of 1/
1,000,000 to 1/10,000, although it may not completely be so (Bois et
al., 1995) if pre-existing disease or genetic constitution place a
percentage of the population at greater risk from exposure to
carcinogens. The question of what may be the actual variation in human
susceptibility is one that was discussed in general in the NRC (1994)
report, as well as the NRC report on pesticides in children and infants
(NRC, 1993b). NRC has recommended research on the question, and EPA and
other agencies are conducting such research. Given the current state of
knowledge, EPA will assume that the linear default procedure adequately
accounts for human variation unless there is case-specific information
for a given agent or mode of action that indicates a particularly
susceptible subpopulation or lifestage, in which case the special
information will be used.
When adequate data on mode of action provide sufficient evidence to
support a nonlinear mode of action for the general population and/or
any subpopulations of concern, a different approach--a reference dose/
reference concentration that assumes that nonlinearity--is used. The
POD is again generally an BMDL when incidence data are modeled. A
sufficient basis to support this nonlinear procedure is likely to
include data on responses that are key events integral to the
carcinogenic process. This means that the POD may be based on these
precursor response data, for example, hormone levels or mitogenic
effects rather than tumor incidence data.
When the mode of action information indicates that the dose-
response function may be adequately described by both a linear and a
nonlinear approach, then the results of both the linear and the
nonlinear analyses are presented. An assessment may use both linear and
nonlinear approaches if different responses are thought to result from
different modes of action or a response appears to be very different at
high and low doses due to influence of separate modes of action. The
results may be needed for assessment of combined risk from agents that
have common modes of action.
Absent data to the contrary, the default assumption is that the
cumulative dose received over a lifetime, expressed as a lifetime
average daily dose or lifetime average daily exposure, is an
appropriate measure of dose or exposure. This assumes that a high dose
of such an agent received over a shorter period of time is equivalent
to a low dose spread over a lifetime. This is thought to be a
relatively public-health-protective option and has some empirical
support (Monro, 1992). A counter example, i.e., effects of short-term,
high exposure levels that result in subsequent cancer development, is
treatment of cancer patients with certain chemotherapeutic agents. When
sufficient information is available to support a different approach, it
can be used. For example, short-term exposure estimates (several days
to several months) may be more appropriate than the lifetime average
daily dose. In these cases, both agent concentration and duration are
likely to be important, because such effects may be reversible at
cessation of very short-term exposures.
Appendix B: EPA's Guidance for Data Quality Assessment
U.S. EPA (U.S. Environmental Protection Agency). (2000d)
Guidance for data quality assessment: practical methods for data
analysis. Office of Environmental Information, Washington, DC. EPA/
600/R-96/084. Available from: http://www.epa.gov/quality/qs-docs/g9-final.pdf
.
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[FR Doc. 05-6642 Filed 4-6-05; 8:45 am]
BILLING CODE 6560-50-C