Multiple Hypotheses Testing Procedures in Clinical Trials and Genomic Studies - Pan, Qing (Frontiers in Public Health, 2013)
We review and compare multiple hypothesis testing procedures used in clinical trials and those in genomic studies. Clinical trials often employ global tests, which draw an overall conclusion for all the hypotheses, such as SUM test, Two-Step test, Approximate Likelihood Ratio test (ALRT), Intersection Union Test (IUT) and MAX test. The SUM and Two-Step tests are most powerful under homogeneous treatment effects, while the ALRT and MAX test are robust in cases with nonhomogeneous treatment effects. Furthermore, the ALRT is robust to unequal sample sizes across endpoints. In genomic studies, stepwise procedures are used to draw marker-specific conclusions and control family wise error rate (FWER) or false discovery rate (FDR) at the same time. FDR refers to the percent of false positives among all significant results and is preferred over FWER in screening high-dimensional genomic markers due to its interpretability. In cases where correlations between test statistics cannot be ignored, Westfall-Young resampling method can be employed to generate the joint distribution of P-values under the null and maintain their correlation structure. Finally, the GWAS from a clinical trial studying microvascular complications among Type 1 diabetes patients is used to illustrate various procedures.