The following principles are excerpted with
permission from the copyrighted book Principles for Evaluating Epidemiologic
Data in Regulatory Risk Assessment, developed by an Expert Panel at
a Conference in London, England, October 1995. Federal Focus Inc.
Expert Panel Co-Chairs: Graham, J.D.; Koo, L.C.; Paustenbach, D.J.;
Expert Panel Members: Ashby, J.; Carlo, G.; Cohen, S.M.; Evans,
J.S.; Holland, W.; Matanoski, G.M.; North, G.W.; Pershagen, G.; Schlesselman,
J.J.; Starr, T.B.; Swenberg, J.A.; Teta, M.J.; Wichmann, E.; Williams,
Federal Focus participants: Kelly Jr., W.J.; Auchter, T.G.; Landeck,
S.; Ploger, W.D. Washington, DC: Federal Focus, Inc. 1996.
Principles for Evaluating Epidemiologic Data in Regulatory Risk Assessment.
Developed by an Expert Panel at a Conference in London, England,
THE PRINCIPLES, PREAMBLES, AND RECOMMENDATIONS FOR FUTURE STUDIES
Preliminary and summary issues to be considered in assessing the utility
of an epidemiologic study for risk assessment:
- a. Were the objectives of the study defined and stated?
- b. Are the data relevant for risk assessment?
- c. Was the study designed to have sufficient power to detect the effect(s)
- d. Were good epidemiological practices followed?
- e. Can the study findings be generalized for statutory regulations?
- f. Were the principles enumerated below followed?
The listing of "preliminary and summary issues" is designed
to help the reviewer to begin focusing on fundamental issues of the study's
utility for risk assessment, and whether the study is suitable for either
or both the hazard identification and dose-response components of a risk
The presence of questions in the format of a checklist in this preliminary
section and under each of the hazard identification principles which follow
does not imply that the principles and checklists can be applied in a mechanical
fashion, that they are intended to produce some kind of numerical "score"
or "grade," or that there are certain minimum quality hurdles
a study must surmount. Nevertheless, when considered in their totality,
the principles and subquestions are intended to assist the risk assessor,
assisted by experts in epidemiology and other relevant disciplines, in forming
an opinion as to the overall quality of the data and the weight they should.
be given in a risk assessment. While nonconformance with any single principle,
or a "No" or "Not Known" answer to any subquestion,
should not eliminate a study from consideration, review of the study in
light of all the principles might result in its being given essentially
no weight in a risk assessment.
A. PRINCIPLES FOR EVALUATING AN EPIDEMIOLOGIC REPORT FOR CAUSE-EFFECT
The numbered principles in this section apply only to the hazard identification
portion of a risk assessment. The questions under each principle are designed
to help elucidate the principle and to assist the expert reviewer in judging
whether the study is consistent with that principle. The subquestions are
framed so that a Yes answer is preferred.
The emphasis in these hazard identification principles is on evaluating
individual studies, and the principles follow a logical progression from
design and study population selection to reporting of results and evaluation
of the results in a risk assessment context. Principle A-6, however, addresses
interpretation of multiple studies through application of the "Bradford
Hill criteria;" and Principle B-6 in the dose-response section, concerning
meta-analysis, applies to consideration of multiple studies for hazard identification
purposes as well as for dose-response purposes.
It must be emphasized that it is intended that application of these principles
and interpretation of the data for risk assessment should be done by the
risk assessor with the assistance of expert epidemiologists, and preferably
with the assistance of a multidisciplinary team that includes not only epidemiologists,
but also experts from other relevant disciplines, such as toxicology, medicine,
biology, and industrial hygiene.
Finally, it is recognized that these principles set high standards, and
that it is unlikely that any individual study can be considered perfect.
The principles were drafted not only for the purpose of evaluating existing
studies, but also with the hope that they will encourage greater rigor in
future studies that are likely to be used in regulatory risk assessment.
[NOTE: In the book, lettered sub-principles are followed by boxes
to check "yes," "no," "unknown," or "not
Principle A-1. The population studied should
be pertinent to the risk assessment at hand, and it should be representative
of a well-defined underlying cohort or population at risk.
- a. Were study subjects representative of exposed and unexposed persons
(cohort study), or of diseased and non-diseased persons (case-control study)?
- b. To minimize bias, were exposed and unexposed persons comparable
"at baseline" (cohort study), or were cases similar to controls,
prior to exposure, with respect to major risk factors for the disease or
condition under study?
Principle A-2. Study procedures should be described
in sufficient detail, or available from the study's written protocol, to
determine whether appropriate methods were used in the design and conduct
of the investigation.
- a. To minimize the potential for bias, were interviewers and data collectors
blind to the case/control status of study subjects and to the hypothesis
- b. Were there procedures for quality control in place for all major
aspects of the study's design and implementation (e.g., ascertainment and
selection of subjects for study, methods of data collection and analysis,
- c. Were the effects of nonparticipation, a low response rate, or loss
to follow-up taken into account in producing the study results?
Principle A-3. The measures of exposure(s)
or exposure surrogates should be: (a) conceptually relevant to the risk
assessment being conducted; (b) based on principles that are biologically
sound in light of present knowledge; and (c) properly quantitated to assess
- a. Were well-documented procedures for quality assurance and quality
control followed in exposure measurement and assessment (e.g. calibrating
instruments, repeat measurements, re-interviews, tape recordings of interviews,
- b. Were measures of exposure consistent with current biological understanding
of dose (e.g., with respect to averaging time, dose rate, peak dose, absorption
via different exposure routes)?
- c. If there is uncertainty about appropriate exposure measures, was
a variety of measures used (e.g, duration of exposure, intensity of exposure,
- d. If surrogate respondents were the source of information about exposure,
was the proportion of the data they provided given, and were their relationships
to the index subjects described?
- e. To improve study power and enhance the generalizability of findings,
was there sufficient variation in the exposure among subjects?
- f. Were correlated exposures measured and evaluated to assess the possibility
of competing causes, confounding, and potentiating effects (synergy)?
- g. Were exposures measured directly rather than estimated? If estimated,
have the systematic and random errors been characterized, either in the
study at hand or by reference to the literature?
- h. Were measurements of exposure or human biochemical samples of exposure
made? Was there a distinction made between exposures estimated by emission
as opposed to body absorption?
- i. If exposure was estimated by questionnaire, interview, or existing
records, was reporting bias considered, and was it unlikely to have affected
the study outcome?
- j. Was there an explanation/understanding of why exposure occurred,
the context of its occurrence, and the time period of exposure?
Principle A-4. Study outcomes (endpoints) should
be clearly defined, properly measured, and ascertained in an unbiased manner.
- a. Was the outcome variable a disease entity or pathological finding
rather than a symptom or a physiological parameter?
- b. Was variability in the possible outcomes understood and taken into
account -- e.g., various manifestations of a disease considering its natural
- c. Was the method of recording the outcome variable(s) reliable --
e.g., if the outcome was disease, did the design of the study provide for
recording of the full spectrum of disease, such as early and advanced stage
cancer; was a standardized classification system, such as the International
Classification of Diseases, followed; were the data from a primary or a
- d. Has misclassification of the outcome(s) been minimized in the design
and execution of the study? Has there been a review of all diagnoses by
qualified medical personnel, and if so, were they blinded to study exposure?
Principle A-5. The analysis of the study's
data should provide both point and interval estimates of the exposure's
effect, including adjustment for confounding, assessment of interaction
(e.g, effect of multiple exposures or differential susceptibility), and
an evaluation of the possible influence of study bias.
- a. Was there a well-formulated and well-documented plan of analysis?
If so, was it followed?
- b. Were the methods of analysis appropriate? If not, is it reasonable
to believe that better methods would not have led to substantially different
- c. Were proper analytic approaches, such as stratification and regression
adjustment, used to account for well-known major risk factors (potential
confounders such as age, race, smoking, socio-economic status) for the
disease under study?
- d. Has a sensitivity analysis been performed in which quantitative
adjustment was made for the effect of unmeasured potential confounders,
e.g., any unmeasured, well-established risk factor(s) for the disease under
- e. Did the report avoid selective reporting of results or inappropriate
use of methods to achieve a stated or implicit objective? For example,
are both significant and non-significant results reported in a balanced
- f. Were confidence intervals provided in the main and subsidiary analyses?
Principle A-6. The reporting of the study should
clearly identify both its strengths and limitations, and the interpretation
of its findings should reflect not only an honest consideration of those
factors, but also its relationship to the current state of knowledge in
the area. The overall study quality should be sufficiently high that it
would be judged publishable in a peer-reviewed scientific journal.
- a. Were the major results directly related to the a priori hypothesis
- b. Were the strengths and limitations of the study design, execution,
and the resulting data adequately discussed?
- c. Is loss to follow-up and non-response documented? Was it minimal?
Has any major loss to follow-up or migration out of study been taken into
- d. Did the study's design and analysis account for competing causes
of mortality or morbidity which might influence its findings?
- e. Were contradictory or implausible results satisfactorily explained?
- f. Were alternative explanations for the results seriously explored
- g. Were the Bradford Hill criteria (see Appendix B) for judging the
plausibility of causation (strength of association, consistency within
and across studies, dose response, biological plausibility, and temporality)
applied when interpreting the results?
- h. What are the public health implications of the results? For example,
are estimates of absolute risk given, and is the size of the population
at risk discussed?
B. PRINCIPLES FOR USING HUMAN AND ANIMAL DATA IN DOSE-RESPONSE EVALUATION
Proceeding to application of the dose-response principles assumes that
the existence of a hazard has been adequately established under the above
principles. On the other hand, adequate establishment of hazard, even with
a showing of strong and consistent association, does not necessarily mean
there are sufficient data for use in dose-response evaluation. The dose-response
principles assume that there is a need for dose-response extrapolation because
no individual epidemiologic study provides sufficient high-quality information
on dose-response to reach conclusions about dose-response at the exposure
levels being addressed in the regulatory risk assessment.
These principles also assume that higher quality data are required for
dose-response evaluation than for hazard identification, and that data used
for dose-response should meet some minimum standards or quality hurdles.
In other words, the reviewer and risk assessor should answer the basic question
of whether the epidemiologic data, in an individual study or cumulatively,
are adequate for use in dose-response evaluation. There is no formula or
quantitative weighting scheme prescribed for making this judgment.
The principles address not only the use of epidemiologic data by themselves,
but also their use in combination or conjunction with animal and/or biologic
data. Consequently, there is an even greater need than in the hazard identification
phase for scientists from relevant disciplines other than epidemiology to
work with the risk assessor to interpret the data.
If epidemiologic data adequate for dose-response evaluation are not available,
and a risk assessment is being developed for use in making an important
regulatory decision, and if it is feasible to develop new epidemiologic
data, or to extract new data from existing studies, an effort should be
made to develop and provide good epidemiologic dose-response data that can
be used together with, or in preference to, high-dose animal data.
Principle B-1. Dose-response assessment should
include a range of reasonable dose measures, explain why any were rejected,
and provide a rationale if any particular dose metric is preferred. In evaluations
of both human and animal data, several different measures of dose should
be evaluated (if possible).
Principle B-2. In the selection of a dose-response
model, the greatest weight should be given to models that fit the observed
animal and human data and are consistent with the biologically relevant
mode(s) of action (genotoxic, nongenotoxic, unclassified). When mechanistic
knowledge is uncertain or limited, several plausible dose-response models
should be considered and the most plausible ones, based on available data
and professional judgment, should generally be used in dose-response evaluation.
Principle B-3. When extrapolating cancer risk
to exposure levels below the observable range, mechanistic data should be
used to characterize the shape of the dose-response function.
Principle B-4. When the available epidemiologic
data are not adequate to perform dose-response analyses, causing low-dose
estimates of risk to be derived exclusively from animal data, every effort
should still be made to use the available human data in assessing the validity
of low-dose risk estimates. To the extent feasible, heterogeneity in the
human population should be accounted for. Whenever feasible, human data
on metabolic biomarkers and other biological measures should be employed
to adjust the risk estimates for known differences between species and between
high and low doses. If possible, data on susceptibility should be included.
Principle B-5. When epidemiologic studies are
selected for dose-response assessment, higher quality studies should be
given preference, especially those with precise and accurate exposure information.
The availability of information with respect to timing of exposure and response
(time/age of first exposure, intensity of exposure, time to tumor), adjustment
for confounding variables, and potential interaction with other effect modifiers
is particularly important.
Principle B-6. A properly conducted meta-analysis,
or preferably an analysis based on the raw data in the original studies,
may be used in hazard identification and dose-response evaluation when such
combination includes an evaluation of individual studies and an assessment
of heterogeneity. The combined results ought to provide, more than any single
study, precise risk estimates over a wider range of doses. Before using
these tools, the gains should be judged sufficient to justify potential
errors in inference resulting from combining studies of dissimilar design
Principle B-7. When epidemiological data are
used in dose-response assessment, a quantitative sensitivity analysis should
be conducted to determine the potential effects on risk estimates of confounders,
measurement error, and other sources of uncontrolled bias in study design.
Principle B-8. Scientific understanding of
differentials in human susceptibility to disease (racial/ethnic/gender/genetic
differences, genetic polymorphisms, etc.) should be used to refine the low-dose
extrapolation procedures when such phenomena are adequately understood.
Principle B-9. To characterize the most important
sources of uncertainty in the final estimate of risk, a quantitative analysis
should be conducted to determine the major sources of uncertainty in dose-response
assessment, including discussion of the prospects that future research might
diminish the various sources of uncertainties.
EPILOGUE TO PRINCIPLES: Questioning of epidemiologist researchers
by risk assessors
- Risk assessors' criticisms and major questions about the methods, analyses,
data, or interpretation of a published report should be directed, whenever
possible, to the epidemiologist(s) responsible for the paper, and they
should be given an opportunity to respond.
- Risk assessors may want access to the study's data set for other analyses
to be used in the risk assessment. This would be done with the consent
and cooperation of the study epidemiologist(s).
RECOMMENDATIONS FOR IMPROVING FUTURE EPIDEMIOLOGIC STUDIES AND THEIR
USE IN REGULATORY RISK ASSESSMENT
Recommendation 1. A commitment to collaboration
should be made by epidemiologists and risk assessors that includes (a) sharing
of raw data where feasible, (b) exchange of protocols and survey instruments,
(c) inclusion of epidemiologists in dose-response modeling exercises, and
(d) care and fairness by risk assessors in the critique of original epidemiologic
Recommendation 2. Future epidemiologic studies
should be funded and designed with the needs of regulatory risk assessors
in mind, including (a) richer exposure information (e.g., age-specific exposure
histories and measures of key confounders), and (b) ample resources for
careful dose-response analyses.
Recommendation 3. Epidemiologic study teams (and the
peer review panels that evaluate them for funding) should include multidisciplinary
expertise from the fields of medicine, toxicology, industrial hygiene, statistics,
and risk assessment, as well as epidemiology.
Recommendation 4. Peer review should be applied
to the use of epidemiologic data in risk assessment, including (a) involvement
of the original epidemiologic investigator(s) when possible, (b) panels
that reflect stature, objectivity, appropriate areas of expertise, and balance
in perspective, and (c) opportunity for public comment, such as that used
by EPA's Science Advisory Board.
Recommendation 5. Reporting of epidemiologic findings
should be responsive, if possible, to the needs of risk assessors, including
(a) documentation of rationales for decisions about how data were grouped
for analysis purposes, (b) clear distinctions between subjects with small
vs. zero exposure, and (c) reporting of extent of pre-testing in multivariate
modeling in order to allow better interpretation of classical statistical
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Principles for Evaluating Epidemiologic Data in Regulatory Risk Assessment
Library of Congress Catalogue No. 96-S8998
International Standard Book No.0-9654148-0-9
Copyright Federal Focus, Inc.® 1996. All rights reserved, except
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