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Win statistics (win ratio, win odds, and net benefit): Noncollapsibility and standardization for randomized clinical
Gaohong Dong1, Margaret Gamalo-Siebers2, Ying Cui3
1iStats Inc., Long Island City, New York, USA.
Journal of Biopharmaceutical Statistics
|February 18, 2026
Summary
Win statistics like the win ratio are generally noncollapsible across clinical trial data types. Stratified win statistics offer a standardization approach for complex outcome analyses, addressing concerns highlighted by the FDA.
Area of Science:
- Clinical Trials Methodology
- Biostatistics
- Health Outcomes Research
Background:
- Win statistics, including the win ratio and win odds, are prevalent in clinical trial design and analysis across various disease areas.
- These statistics are crucial for evaluating treatment efficacy, particularly in cardiovascular diseases, oncology, and diabetes.
- Despite extensive research on statistical inference, the noncollapsibility of win statistics remains under-investigated, a critical issue noted in recent FDA guidance.
Purpose of the Study:
- To investigate the noncollapsibility of win statistics (win ratio, win odds, net benefit) in clinical trial data.
- To evaluate the collapsibility of these statistics across binary, continuous, and time-to-event data types.
- To propose solutions for analyzing prioritized multiple outcomes in the presence of noncollapsibility.
Main Methods:
- Analysis of win statistics' collapsibility using simulated and real-world clinical trial data.
- Examination of win ratio, win odds, and net benefit across binary, continuous, and time-to-event data structures.
- Application of statistical inference methods to assess noncollapsibility properties.
Main Results:
- The win ratio was found to be noncollapsible for all three data types (binary, continuous, time-to-event).
- Win odds and net benefit demonstrated collapsibility for binary data but were noncollapsible for continuous and time-to-event data.
- Overall, win statistics exhibit general noncollapsibility, necessitating careful interpretation and analysis.
Conclusions:
- Win statistics are generally noncollapsible, impacting their interpretation in clinical trial analysis.
- Stratified win statistics are proposed as a robust standardization method for analyzing prioritized multiple outcomes.
- This approach is particularly valuable in scenarios where noncollapsibility is a significant concern, aligning with FDA recommendations.
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