This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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283
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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Abstract - #306940 |
Title:
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Application of Bayesian Joint Modeling of Time-to-Event and Patient-Reported Outcomes in an Oncology Clinical Trial
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Author(s):
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Luping Zhao*+ and Wei Shen and Haoda Fu and Michelle Denise Hackshaw and Mark E. Boye
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Companies:
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Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company and Eli Lilly and Company
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Address:
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Eli Lilly and Company, Drop code 6831, Indianapolis, IN, 46278,
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Keywords:
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Bayesian approach ;
Joint modeling ;
Oncology clinical trial ;
Patient reported outcomes ;
Time-to-event data
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Abstract:
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The measurement of patient-reported outcomes (PROs) has gained substantial attention in recent oncology clinical research. Although several joint models of longitudinal and time-to-event data have been developed in recent years, few research studies have been conducted to show the association between PROs and time-to-event endpoints, and to evaluate and interpret differences between treatment arms. We developed a Bayesian joint model where latent variables link the repeatedly measured PROs and time-to-event outcomes. We applied the model to a randomized oncology clinical trial, and compared our results to those obtained from the standard methods, which analyze PROs and time-to-event endpoints separately. Our results provided better understanding of the treatment effects through their associations with both PROs and time-to-event outcomes.
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