Given the importance of addressing multiplicity issues in confirmatory clinical trials, several recent publications focused on the general goal of identifying most appropriate methods for multiplicity adjustment in each individual setting. This goal can be accomplished using the Clinical Scenario Evaluation approach. This approach encourages trial sponsors to perform comprehensive assessments of applicable analysis strategies such as multiplicity adjustments under all plausible sets of statistical assumptions using relevant evaluation criteria. This two-part paper applies a novel class of criteria, known as criteria based on multiplicity penalties, to the problem of evaluating the performance of several candidate multiplicity adjustments. The ultimate goal of this evaluation is to identify efficient and robust adjustments for each individual trial and optimally select parameters of these adjustments. Part I deals with traditional problems with a single source of multiplicity. Two case studies based on recently conducted Phase III trials are used to illustrate penalty-based approaches to evaluating candidate multiple testing methods and constructing optimization algorithms.
Keywords: Clinical scenario evaluation; Type I error rate; clinical trial optimization; multiple testing.