title: Flexible matching strategies to increase power and efficiency to detect and estimate gene-environment interactions in case-control studies.
abstract: Lack of power is a pertinent problem in many case-control studies of gene-environment interactions. The authors recently introduced the concept of flexible matching strategies with varying proportions of a matching factor among selected controls (degree of matching) to increase the power and efficiency of case-control studies. In this study, they extended the concept of flexible matching strategies to the field of gene-environment interactions. They assessed the power and efficiency of such studies to detect and estimate gene-environment interactions under a variety of assumptions regarding the prevalence and effects of the environmental exposure and the genetic susceptibility as well as their association in the population. For each set of parameters, 10,000 case-control studies were simulated using varying degrees of matching. Traditional frequency matching increased the power and precision in most scenarios, but even greater gains were often obtained by increasing the prevalence of the environmental exposure in controls above the one in cases. The authors concluded that flexible matching strategies can increase the power and efficiency of case-control studies to detect and estimate gene-environment interactions compared with traditional frequency matching and therefore might help to alleviate the notorious lack of power of these studies in specific situations.
authors.affiliation: Department of Epidemiology, German Centre for Research on Ageing, Heidelberg, Germany. sturmer@dzfa.uni-heidelberg.de
authors.forename: Til
authors.initials: T
authors.lastname: Stürmer
authors.forename: Hermann
authors.initials: H
authors.lastname: Brenner
mesh_terms: D016022:Case-Control Studies; D003198:Computer Simulation; D004781:Environmental Exposure; D004812:Epidemiologic Methods; D020022:Genetic Predisposition to Disease; D006801:Humans; D012107:Research Design; D012307:Risk Factors; D018401:Sample Size; D013223:Statistics as Topic