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

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, includin g 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 additio nal 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 signific ance level for the trial. We describe and compare two methods for testing p rimary and secondary endpoints, accounting for their hierarchical nature-th e ordering preference. Both methods are sequential, in the sense that the s econdary endpoint is only tested when the primary outcome fails to reach si gnificance. 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 met hod performs as well as the global test method in most cases, and even bett er in some cases. (C) Elsevier Science Inc. 2000.