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Abstract Details
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Activity Number:
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647
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 4, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Government Statistics
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| Abstract - #301566 |
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Title:
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Clinical Trial Designs for Testing Biomarker-Based Personalized Therapies
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Author(s):
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Tze Leung Lai and Philip Lavori and Mei-Chiung Shih*+ and Branimir Sikic
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Companies:
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Stanford University and Stanford University and Veterans Administration and Stanford University
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Address:
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, , 94025,
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Keywords:
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Adaptive randomization ;
Biomarkers ;
Generalized likelihood ratio statistics ;
Group sequential designs ;
Personalized therapies ;
Ovarian cancer
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Abstract:
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Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the validation of biomarker-based personalized therapies. We develop a new clinical trial design to address some of these issues. The goal is to capture the strengths of the frequentist and Bayesian approaches to this problem, and to circumvent their limitations. We use recent developments in group sequential testing and adaptive randomization to derive a novel clinical trial design for the problem. Simulation studies show substantial improvements of the proposed design over traditional randomized clinical trial designs.
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