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Activity Number:
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277
- Statistical Methods for Composite Time-To-Event Endpoints
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Type:
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Invited
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Date/Time:
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Tuesday, July 30, 2019 : 8:30 AM to 10:20 AM
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Sponsor:
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Lifetime Data Science Section
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Abstract #300163
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Presentation
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Title:
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Some Meaningful Weighted Win Loss Statistics
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Author(s):
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Xiaodong Luo* and Hui Quan
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Companies:
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and Sanofi US
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Keywords:
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win ratio;
RMST;
multiple testing;
composite endpoints
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Abstract:
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It is often difficult to summarize treatment effect in survival trials in the presence of non-proportional hazards. It is even harder to do so when there is more than one endpoints (PFS and OS, for example) in the trial. In this talk, I will introduce some meaningful treatment effect measurements that are derived from weighted log-rank and weighted win loss statistics. I will illustrate that the use of such statistics will provide a coherent way to conduct hypothesis testing and treatment effect estimation in survival trials. Such statistics can also alleviate the multiple testing issues of the commonly used weighted log-rank statistics and the recently proposed (un-weighted) win ratio statistic in the presence of non-proportional hazards and/or multiple endpoints. I will also demonstrate some potential power loss in hypothesis testing as a trade-off for having a more interpretable test statistic.
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Authors who are presenting talks have a * after their name.
