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Activity Number: 645
Type: Contributed
Date/Time: Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #313729 View Presentation
Title: Flexible Multivariate Methods for Binary-Event or Ordinal Composite Endpoints
Author(s): Edward Mascha*+
Companies: Cleveland Clinic
Keywords: average relative effect ; composite outcome ; multivariate analysis ; generalized estimating equations ; treatment effect heterogeneity ; empirical power
Abstract:

Clinical research studies comparing 2 or more treatments often include a composite primary endpoint comprising several binary components, such as distinct postoperative complications. Ideally, components have similar clinical severity and frequency and are similarly affected by treatment. When not true this leads to serious interpretation issues. Although not a substitute for prudent planning, multivariate (i.e., multiple outcomes per subject) methods are generally more powerful, flexible, and easier to interpret than standard methods which collapse the components into a single number. The multivariate framework facilitates severity weighting of components, assessment of heterogeneity of effects across components, and assuming either a common or distinct treatment effects. We highlight a multivariate distinct effects test of the average of the relative treatment effects (ARTE) across components. This improves existing multivariate methods by not allowing the overall effect estimate to be driven by highest frequency component(s), a key issue with composite endpoints. We assess the relative powers of the methods through simulations. Methods are demonstrated using 2 clinical trials.


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