Statistical methods and application cases examples for multiplicity issues in multiple endpoints clinical trials

Abstract

Performing multiple tests without adjusting the test level results in a higher-than-intended overall familywise error rate (FWER). This phenomenon is known as the multiplicity problem. In this paper, we  first introduced the mechanism of multiplicity problem based on the classification and characterization of clinical endpoints. Then,  strategies and methods to solve the multiplicity problem were introduced, including the parallel strategy/single-step method, the sequential strategy/multistep method/stepwise method, and their combinations. The results of different analytic strategies may vary. The practical application of the above common strategies and statistical methods were introduced through the case studies of domestic and foreign investigator initiated clinical trial. Multiplicity adjustment for multiple endpoints in clinical trials can be achieved by a single strategy or a combination of strategies. Depending on the selected strategy or combination, the statistical  methods and significance level (denoted as α) for each test hypothesis are determined to effectively control the multiplicity problem.