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American Journal of Epidemiology
Copyright O 2000 by The Johns Hopkins University School of Hygiene and Public Health
All rights reserved
Vol. 151, No. 10
Printed In U.SA.
Dr. Shapiro Responds to Dr. Hertz-Picciotto
Samuel Shapiro
This response follows Dr. Hertz-Picciotto's order
(1). She represents me as advising that "...if bias can
explain small associations, we should give up our scientific pursuit of the...issue" (2, p. 946). I advise
nothing of the sort. On the contrary, well-grounded
hypotheses should be pursued with better methods
and in different populations. Under causal assumptions, stronger associations may then be evident.
1. Hertz-Picciotto states that hypothesized bias
"...should be subject to the same scrutiny as the
hypothesis of causality" (1, p. 946). That requirement
is novel. Data to evaluate possible bias, when available, are useful, but it is seldom possible to demonstrate that any given finding is biased. Causality may
nevertheless be in doubt. If there is reasonable evidence to judge that bias may explain an association,
the onus is on the proponent of causality to show that
it does not; otherwise, its possible existence must be
conceded. In the collaborative reanalysis (3, 4), for
example, most of the data were derived from interview- or questionnaire-based case-control studies. As
a matter of judgment, information bias clearly could
not be excluded. That possibility was acknowledged
by the investigators and is now acknowledged by
Hertz-Picciotto, without the requirement of equal
scrutiny.
For selection bias, Hertz-Picciotto does demand
equal scrutiny. Yet the evidence to support the possible existence of that bias, some of it published (5), is
again compelling. Further evidence is that gynecologists who prescribe oral contraceptives are expected
to conduct breast examinations (6), as are family
planning services (7); for services that receive federal
support, annual examinations are mandatory (8). A
convenient time to conduct examinations is when
oral contraceptive prescriptions are renewed;
nonusers do not require renewals, and breast examinations are optional.
As for past use, the issue is not whether physicians
question women about it, but whether ex-users systematically undergo more screening than do never
users. Given the widespread publicity about breast
cancer risk, the a priori presumption must be that
they do. Hertz-Picciotto interprets mammography
data from the collaborative reanalysis (4) as suggesting the contrary. Those data are uninterpretable
because of the following limitations in some or all
of the included studies: incomplete data; selection
bias; failure to distinguish between screening mammographies, as against mammographies done in
diagnostic workups after breast cancer has already
been diagnosed; and failure to take into account
other methods of screening (i.e., examination and
self-examination).
Setting those matters aside, it is not even necessary
to assume greater surveillance among ex-users. In the
hypothetical study, assume that the only bias is the
identification of one additional, otherwise occult case
of breast cancer among current oral contraceptive
users: The relative risk is 1.20 and is higher than the
estimates in any of the remaining time categories.
2. I elect not to respond to Dr. Hertz-Picciotto's
proposition that "...the 'null' situation might be far
lower than a relative risk of 1.0" (1, p. 947).
3. My commentary is confined to a consideration
of one of the well-known criteria for causal inference
in epidemiology (9, 10), the magnitude of the association. This does not mean that I base my judgment
solely on that criterion. On the basis of other criteria,
biologic plausibility in particular, unlike HertzPicciotto, I consider the totality of the evidence concerning a possible connection between oral contraceptives and breast cancer to be suggestive and not at
all unconvincing—the absence of a dose or duration
effect notwithstanding. For that reason and because
the existing epidemiologic evidence is inconclusive,
more research is needed.
Based on a considerable body of evidence, some of
it mentioned by Hertz-Picciotto, it is possible, perhaps even likely, that passive smoking increases the
Received for publication January 4, 2000, and accepted for publication January 7, 2000.
From the Slone Epidemiology Unit, Boston University School of
Medicine, Brookline, MA, and the Division of Epidemiology,
Columbia School of Public Health, New York, NY.
Reprint requests to Prof. Samuel Shapiro, Division of
Epidemiology, Columbia School of Public Health PH18-107, 600
West 168th Street, New York, NY 10032 (e-mail: sshapiro® slone.
bu.edu).
949
950
Shapiro
risk of lung cancer. However, again, for a relative risk
of 1.26, bias cannot be excluded.
In any properly conducted epidemiologic study, it
is necessary to assess all possible biases, upward or
downward. For small associations, doing so would
not help to distinguish between bias and causation.
4. I do not contend that "...patterns of systematic
biases are.. .uniform across the field of 'small associations,'" and my generalizations do not "...imply nearuniversality" (1, p. 947). Assume, for the argument,
that in the collaborative reanalysis the exposures were
ascertained from objective sources, high participation
rates were achieved, the study question was concealed,
and follow-up was complete. Bias could still have
accounted for the observed associations.
With regard to the presentation of relative risks to
the second decimal place, it does not matter whether
doing so should be considered pseudoprecision or
pseudoaccuracy. It is pseudoscience.
Hertz-Picciotto suggests that we sometimes invoke
unmeasured confounders too readily. If any confounder so invoked may plausibly explain an association, causality cannot be inferred until it is ruled out.
Finally, no one disputes the desirability of
improved methods. What is at issue is whether such
improvements can disentangle bias and causation
when associations are small. If they are small
enough, I contend that making the distinction is
beyond the resolving power of nonexperimental
research. If Hertz-Picciotto believes otherwise, she
should demonstrate that my contention is incorrect.
REFERENCES
1. Hertz-Picciotto I. Invited commentary: Shifting the burden of
proof regarding biases and low-magnitude associations. Am J
Epidemiol 2000; 151:946-8.
2. Shapiro S. Bias in the evaluation of low-magnitude associations: an empirical perspective. Am J Epidemiol 2000; 151:
939-45.
3. Collaborative Group on Hormonal Factors in Breast Cancer.
Breast cancer and hormonal contraceptives. Lancet 1996;347:
1713-27.
4. Collaborative Group on Hormonal Factors in Breast Cancer.
Breast cancer and hormonal contraceptives. Contraception
1996;54(Suppl.):lS-106S.
5. Skegg DCG. Potential bias in case-control studies of oral contraceptives and breast cancer. Am J Epidemiol 1988; 127:
205-12.
6. American College of Obstetricians and Gynecologists
Important facts about the pill. Patient information booklet R39. Chicago, EL: American College of Obstetricians and
Gynecologists, 1977.
7. Planned Parenthood Federation of North America, Inc. You
and the pill. Item no. 1562. New York, NY: Planned
Parenthood Federation of America, Inc., 1993.
8. US Department of Health and Human Services. 1980. Program
Guidelines for Project Grants for Family Planning Services.
Rockville MD: US Public Health Service, 1980.
9. Hill AB. The environment and disease: association or causation? Proc R Soc Med l965;58:295-300.
10. Susser M. What is a cause and how do we know one? A grammar for pragmatic epidemiology. Am J Epidemiol 1991; 133:
635-48.
Am J Epidemiol
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