JSM 2004 - Toronto

Abstract #301724

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Activity Number: 343
Type: Contributed
Date/Time: Wednesday, August 11, 2004 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #301724
Title: Modeling the Relationship between Two Correlated Survival Outcomes
Author(s): Amita K. Manatunga*+ and Ying Guo
Companies: Emory University and Emory University
Address: Dept. of Biostatistics, Atlanta, GA, 30322,
Keywords: correlated survival times ; agreement ; cancer epidemiology
Abstract:

Often, disease occurrence time of the same subject can be measured by using two different methods. It is of interest to compare the disease free rates between the two methods and to determine whether both methods measure disease freedom in the same manner for each subject. To achieve these goals, we model the relationship between event times and its association to covariates. In addition, we propose several indices to quantify the agreement between the event times and discuss their statistical properties. We derive the relationship of these indices to commonly used odds ratio and discuss their interpretations. Finally, we illustrate our results with a prostate cancer epidemiology study where patients with prostate cancer are treated with simultaneous radiotherapy and their prostate specific antigen is measured by two definitions every six months after the treatment.

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