Sample Size to Test for Interaction Between a Specific Exposure and a Second Risk Factor in a Pair-Matched Case-Control Study

We discuss a sample size calculation for a pair-matched case-control study to test for interaction between a specific exposure and a second risk factor. The second risk factor could be either binary or continuous. An algorithm for the calculation of sample size is suggested which is based on a logistic regression model that relates the logarithm of the disease-exposure odds ratio to the second risk factor. This problem is motivated by a study comparing the prevalence of GP-IIIa Pl^A2 polymorphism (the exposure) in individuals with and without myocardial infarction (case-control). One of the hypotheses in this study is whether or not there is an interaction between the prevalence of GP-IIIa Pl^A2 polymorphism and a second risk factor such as smoking status and homocysteine level. We introduce the algorithm in detail with several numerical examples