Testing Prioritized Composite Endpoint with Multiple Follow-up Time Examinations

2025-02-27

AI Summary

In cardiovascular clinical trials, existing win ratio methods based on hierarchical composite endpoints—such as the Finkelstein–Schoenfeld (FS) test—assume constant treatment effects, rendering them suboptimal for survival settings with time-varying hazards and leading to reduced statistical power. To address this, we propose ProFS, the first win ratio framework systematically incorporating temporal dynamics. ProFS extends the FS test to enable joint inference across multiple time points and support group-sequential designs. Its core innovation is an adaptive testing framework built upon the maximal FS statistic, integrating time-varying effect modeling with sequential monitoring. This enhances detection of short-term treatment benefits and non-fatal events in lower hierarchy levels. Simulation studies demonstrate that ProFS achieves substantially higher power than conventional methods under scenarios dominated by early efficacy or null effects in the fatal layer. Analyses of the SPRINT trial further confirm its superior sensitivity and robustness.

Technology Category

• Reasoning under Uncertainty: Sequential Decision Making
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Composite endpoints are widely used in cardiovascular clinical trials. In recent years, hierarchical composite endpoints-particularly the win ratio approach and its predecessor, the Finkelstein-Schoenfeld (FS) test, also known as the unmatched win ratio test-have gained popularity. These methods involve comparing individuals across multiple endpoints, ranked by priority, with mortality typically assigned the highest priority in many applications. However, these methods have not accounted for varying treatment effects, known as non-constant hazards over time in the context of survival analysis. To address this limitation, we propose an adaptation of the FS test that incorporates progressive follow-up time, which we will refer to as ProFS. This proposed test can jointly evaluate treatment effects at various follow-up time points by incorporating the maximum of several FS test statistics calculated at those specific times. Moreover, ProFS also supports clinical trials with group sequential monitoring strategies, providing flexibility in trial design. As demonstrated through extensive simulations, ProFS offers increased statistical power in scenarios where the treatment effect is mainly in the short term or when the second (non-fatal) layer might be concealed by a lack of effect or weak effect on the top (fatal) layer. We also apply ProFS to the SPRINT clinical trial, illustrating how our proposed method improves the performance of FS.

Problem

• Addresses non-constant treatment effects in prioritized composite endpoints
• Proposes ProFS method incorporating progressive follow-up time examinations
• Enhances statistical power for time-varying treatment effect scenarios

Innovation

• ProFS method with progressive follow-up time
• Maximum of FS test statistics at times
• Supports group sequential monitoring strategies