Death due to lung cancer (as noted on the death certificate) is the outcome of interest. Thus, the line starts at the age the miner was enrolled and ends at the age that the worker is known to have died or at age of last contact if alive. In other words, at each age on the line, the miner meets the eligibility requirements for cohort membership (eg, uranium miner in the 4-state mining area during 1950–1960 enrolled by a United States Public Health Services researcher) and lung cancer death status is known. Each horizontal line represents the ages during which the given miner was under observation or at risk for lung cancer death. Risk Set Representation of Cohort Dataįigure 1A depicts basic information for miners in the underlying cohort. 13–15 Although radon exposure has been estimated for all miners in this cohort, we consider a hypothetical situation in which the only radon exposure–related information available on cohort members is the dates of start and end of mining.

The Colorado Plateau uranium miners cohort formed the basis of a study of radon exposure and lung cancer mortality and has been used extensively both to characterize the radon–lung cancer association and as a methodologic example. 11,12 NESTED CASE-CONTROL STUDIES: A BRIEF OVERVIEW Throughout, we will illustrate the concepts and methods using the Colorado Plateau uranium miners cohort. 4 Thus, although a flawed study design can in general result in biased estimation, with an empirical evaluation, one can explore the magnitude of such potential bias in the particular study in question. This approach can be used to evaluate study design validity, investigate the behavior of estimates under model misspecification, and provide sample size and power calculations.Īs pointed out by Deubner et al, an important advantage of an empirical analysis is that the results are specific to the cohort that serves as the basis for the case-control study. Third, we provide a valid approach to empirical evaluation of nested case-control study designs and analysis methods. In particular, we review their method of empirical investigation and show why it not a valid way to evaluate bias questions in SRS designs. Second, we examine the evidence presented by Deubner et al that the SRS design can be biased when evaluating lagged exposure variables.

First, we give a heuristic description of the nested case-control methodology and provide some intuition about why the approach is valid for assessing exposure–disease associations. 10 Noting that methods to empirically evaluate potential study design biases within the context of existing cohort data have not been described, Deubner et al 4 proposed an approach which they then applied to a cohort of beryllium workers to illustrate problems that they contend arise in SRS studies. However, the repeated assertion of bias in the SRS design has raised concerns in the occupational health community that “tried and true” case-control methods may be flawed. 1–5 Given the theoretical understanding of the validity of the standard nested case-control design, in which case-control sets consist of the case and a simple random sample of controls from the risk set 6–9 (and which we will henceforth refer to as the “simple random sampling case-control” design) such contentions might be dismissed as untenable.

Nonetheless, a number of articles and letters have appeared recently asserting that the nested case-control study design is susceptible to a form of study design bias. The nested case-control design is well established as an epidemiologic study design.

Case control study