The identification of confounders in case-control studies

THE SELECTION of a control group for a case-control study is probably the most important and most difficult decision confronting an investigator. Although there are a number of sources from which controls may be obtained, they are usually chosen either from among other patients at the hospital where the cases are identified (hospital-based) or from among healthy members of the same communities in which the cases reside (population-based). In the preceding paper Stavraky and Clarke report a recent case-control study which used both hospital and population-based controls. The authors compare these two control groups in the hope of clarifying some of the issues involved in choosing between them. However, the study is limited and does not appreciably add to our understanding of the issues involved in choosing between hospital and population-based controls. The first limitation is that the hospital controls are from London (Ontario) while the neighborhood controls are from Ontario. Although each control group may be appropriate for its respective case series, there is no reason to believe that they are comparable to each other. Indeed, controls are usually selected from the same locale as cases because the prevalence of many exposures differs according to geographic area. The authors apparently recognize this problem, in fact, they explain some of the differences between the two control groups on this basis, but choose largely to ignore it. This is not one case-control study with two control groups, but rather two case-control studies each with its own control group. It is not relevant to the evaluation of the choice between hospital or population-based controls. The second limitation of the study is more subtle. It relates to case-control studies in general and to what issues are and are not important in selecting controls. However, to put the discussion in perspectives, I would like first to make a few general comments about case-control studies. Many scientists view case-control studies with extreme skepticism. This skepticism may arise because such studies are perceived as “unnatural” because they look back from effects to causes and because of the difficulties involved in obtaining unbiased estimates of the exposure frequencies of cases and controls. These aspects of case-control studies have led some to maintain that they are inherently non-scientific and that their validity can be enhanced by considering as their goal the duplication of the results of a randomized controlled trial. However, case-control studies differ from randomized controlled trials in that the latter are experimental whereas the former are non-experimental scientific investigations. The goal of a case-control study should be to obtain a valid estimate of the disease frequency among exposed persons relative to that among the non-exposed, not to mimic a randomized trial. This concern with their supposed unscientific nature has fostered a need to do something to enhance their validity and many epidemiologists believe that this need is fulfilled by controlling for many extraneous factors. In fact, the identification and control of confounding has become a preoccupation in case-control studies. However, although much is known about methods for controlling confounding, often little thought is given to what factors need to be controlled in case-control studies.