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Activity Number: 179
Type: Contributed
Date/Time: Monday, July 30, 2012 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract - #304550
Title: Analysis of Recurrent Event Data with Considering Events Duration
Author(s): Kuolung Hu*+ and Qing Xu
Companies: Amgen, Inc. and FDA
Address: One Amgen Center Drive, Thousand Oaks, CA, 91320-1799, United States
Keywords: Poisson regression model ; recurrent event data ; Anderson-Gill Model ; counting process

In some clinical trials, the primary endpoint is repeated occurrences of same or related types of events. Poisson regression and generalized Cox models (Andersen-Gill model and proportional means model (PMM)) are commonly used in analyzing such data. To properly assess the treatment effect on the recurrent event eposides (first and subsequent), whether removing subjects from the risk sets within the subject's events' duration or not have not been reported. We assess the operating features for detecting treatment differences while considering such characteristic. The Metcalfe and Thompson (2006) approach is used to simulate recurrent events data. Based on our simulations, we found only small discordant results between these analyses. The PMM gave more conservative results than the other methods while the occurrence of subsequent events were correlated.

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