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Randomized trials with composite time-to-event outcomes: Is the win ratio approach always the best?
Jingyi Lin1,2, Ludovic Trinquart1,3,4
1Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Journal of Biopharmaceutical Statistics
|March 6, 2026
Summary
Comparing statistical tests for composite time-to-event endpoints in randomized trials, this study found no single best test. Restricted mean time in favor (RMT-IF) and Wei-Lachin tests showed robust power for overall beneficial effects.
Area of Science:
- Biostatistics
- Clinical Trials Methodology
- Survival Analysis
Background:
- Composite time-to-event endpoints are common in clinical trials.
- Traditional methods like time-to-first-event analysis may not fully capture complex endpoint information.
- The win ratio/Finkelstein-Schoenfeld approach offers an alternative but requires careful evaluation.
Purpose of the Study:
- To compare the statistical performance of various tests for composite time-to-event endpoints in randomized trials.
- To evaluate tests based on generalized pairwise comparison (GPC), restricted mean time in favor (RMT-IF), O'Brien, Wei-Lachin, log-rank, MaxCombo, and area under the cumulative event curve.
- To assess empirical power, size, and information utilization across different scenarios.
Main Methods:
- In-depth simulation studies were conducted for a three-component composite endpoint.
- Component-wise treatment effects of varying magnitudes and directions were generated under proportional and non-proportional hazards.
- Empirical power, size, and percentage of information used were evaluated for each test.
Main Results:
- No single test demonstrated uniform superiority in power across all scenarios.
- GPC and RMT-IF tests had reduced power when treatment effects favored less important events or had delayed impact on critical events.
- RMT-IF and Wei-Lachin tests showed robust power for overall beneficial treatment effects, though RMT-IF had a slightly elevated Type I error in small samples.
Conclusions:
- The choice of statistical test for composite time-to-event endpoints depends on the specific treatment effect profile and trial design.
- RMT-IF and Wei-Lachin tests effectively utilize all events and allow for component-wise analysis, showing promise for overall beneficial effects.
- Further research and careful consideration of test characteristics are needed for optimal trial design with composite endpoints.
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