Hierarchical endpoints and win statistics for geromedicine trials

Geroscience has advanced rapidly, yet its clinical translation remains limited. A central barrier is the lack of trial outcomes that capture the multidimensional effects of geroprotective interventions while meeting clinical and regulatory standards. Mortality is objective and regulatorily salient but often impractical. By contrast, surrogate measures of healthspan improve feasibility and may better reflect the quality of extended life, but they are generally considered soft endpoints that require further validation. Here, we propose hierarchical composite endpoints using time-to-worst-event analysis as a pragmatic and scientifically sound compromise. Participant pairs are compared using win statistics according to a prespecified clinical hierarchy, in which more severe and objective clinical events are prioritized, while health surrogates and biomarkers contribute information at lower tiers. When outcome selection, ordering and tie rules are clinically and mechanistically justified and agreed with regulators, this approach may improve geromedicine trial efficiency and allow overall treatment effects to be captured without compromising clinical priorities.