Potential gain in efficiency and power to detect gene-environment interactions by matching in case-control studies

Background: There is growing interest in interactions between genetic and e nvironmental risk factors of disease, but adequate power to detect such int eractions in epidemiologic studies is of concern. The aim of this paper is to quantify the effect of matching on the efficiency of estimation and powe r to detect gene-environment interactions in case-control studies. Methods: Starting from an empirical example in cancer epidemiology, we simulated fr equency matched and unmatched case-control studies for a wide range of assu mptions regarding the prevalence and the effects of an environmental and a genetic factor on disease risk as well as the quality and quantity of the i nteraction between these factors. Simulated studies were analyzed with mult ivariable logistic regression. Results: Matching increased the efficiency a nd power in most scenarios. The gain was most pronounced in scenarios assum ing a low prevalence of the environmental exposure. In such scenarios, equi valent power was only obtained with more than twice as many unmatched than matched controls. Conclusions: Frequency matching for known environmental r isk factors with a low prevalence in the population may increase the effici ency of estimation and power of case-control studies to detect gene-environ ment interactions considerably. Investigators should weigh the gain in effi ciency and power against known potential disadvantages of matching. Genet. Epidemiol. 18:63-80, 2000. (C) 2000 Wiley-Liss, Inc.