Estimating significance level and power comparisons for testing multiple endpoints in clinical trials

Abstract

Clinical trials generally include several outcome measures of interest for assessing treatment efficacy and harm. Traditionally a single measure, the primary outcome, is selected and used as the basis for the design, including sample size and power. Secondary outcomes are then generally ordered with respect to their clinical relevance and importance. While this has become the traditional paradigm, recent trials have suggested the need for additional approaches. In this setting, two outcomes are viewed as key, either one being sufficient for proof of efficacy, but with an ordering of preference. The basic question, in such cases, is how to control the overall significance level for the trial. We describe and compare two methods for testing primary and secondary endpoints, accounting for their hierarchical nature-the ordering preference. Both methods are sequential, in the sense that the secondary endpoint is only tested when the primary outcome fails to reach significance. The first method uses a global test for the combination of the primary and secondary endpoints, while the second uses a partial Bonferroni correction. Simulation results indicate that the Bonferroni adjustment method performs as well as the global test method in most cases, and even better in some cases.