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Activity Number: 672
Type: Invited
Date/Time: Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
Sponsor: Pharmaceutical Research and Manufacturers of America
Abstract #318345
Title: Large Sample Inference for a Win Ratio Analysis of a Composite Outcome
Author(s): Ionut Bebu* and John M. Lachin
Companies: The George Washington University and The George Washington University
Keywords: composite outcomes ; prioritized components ; win difference ; win ratio ; U-statistics
Abstract:

Composite outcomes are common in clinical trials, especially for multiple time-to-event outcomes (endpoints). The standard approach that uses the time to the first outcome event has important limitations. Several alternative approaches have been proposed to compare two treatments, including the proportion in favor of treatment and the win ratio. Tests of significance and confidence intervals in the context of composite outcomes based on prioritized components are obtained using the large sample distribution of certain multivariate multi-sample U-statistics. This non-parametric approach provides a general inference for both the proportion in favor of treatment and the win ratio, and can be extended to stratified analyses and the comparison of more than two groups. The proposed methods are illustrated with time-to-event outcomes data from a clinical trial.


Authors who are presenting talks have a * after their name.

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