All Times EDT
Keywords: win ratio, composite endpoints, sequential enrichment design,adaptive design
Conventional methods for analyzing composite endpoints in clinical trials often only focus on the time-to-first occurrence of any event in the composite. Therefore, it has inherent limitations because it emphasizes an individual patient’s first event, which can be the outcome of lesser clinical importance. To overcome this problem, the concept of the win ratio for reporting composite endpoints, which accounts for relative priorities of the components and gives appropriate priority to the more clinically important event, has been examined. For example, mortality has a higher priority than hospitalization. In this paper, we evaluate three innovative win-ratio methods (stratified matched, stratified unmatched, and unstratified unmatched) for two and multiple components under binary and survival composite endpoints and then compare them to traditional methods (cox regression, O'Brien rank-sum-type test, contingency table, and Hochberg multiple testing). We also incorporate these approaches in two-stage enrichment designs with the possibility of sample size adaptations to gain efficiency for rare disease studies.