Sample size requirements for matched case‐control studies of gene–environment interaction

TLDR

Gene‑environment interaction is increasingly important in designing new epidemiologic studies. The study presents a method to compute sample size or power for detecting GxE interaction in matched case‑control, case‑sibling, and case‑parent designs. The method calculates expected likelihood ratio test statistics under conditional logistic regression and extends to stratified populations such as multiple ethnic groups. Family‑based designs require fewer matched sets than case‑control for equal power, with the case‑sibling design most efficient for dominant genes and the case‑parent design preferred for recessive genes, and a free software implementation is available online.

Abstract

Consideration of gene-environment (GxE) interaction is becoming increasingly important in the design of new epidemiologic studies. We present a method for computing required sample size or power to detect GxE interaction in the context of three specific designs: the standard matched case-control; the case-sibling, and the case-parent designs. The method is based on computation of the expected value of the likelihood ratio test statistic, assuming that the data will be analysed using conditional logistic regression. Comparisons of required sample sizes indicate that the family-based designs (case-sibling and case-parent) generally require fewer matched sets than the case-control design to achieve the same power for detecting a GxE interaction. The case-sibling design is most efficient when studying a dominant gene, while the case-parent design is preferred for a recessive gene. Methods are also presented for computing sample size when matched sets are obtained from a stratified population, for example, when the population consists of multiple ethnic groups. A software program that implements the method is freely available, and may be downloaded from the website http://hydra.usc.edu/gxe.