Department of Biostatistics Seminar/Workshop Series

A Bayesian Covariate-Adjusted Response-Adaptive Design with Biomarkers for Targeted Therapies in Cancer

KyungMann Kim, PhD

Professor of Biostatistics and Statistics, Director of Biostatistics, Carbone Cancer Center, University of Wisconsin-Madison

Wednesday, January 18, 1:30-2:30pm, MRBIII Room 1220

Pharmacogenomic biomarkers are becoming an important component of a targeted therapy as they can be used to identify patients who are more likely to benefit from treatment. New study designs are required which can effectively evaluate both the prognosis based on pharmacogenomic biomarkers and the therapeutic intervention with targeted therapies.  We propose a Bayesian response-adaptive design that utilizes individual pharmacogenomic profiles and patients' clinical outcomes as they became available during the course of the trial to assign most effective treatment to individual patients.  A series of simulation studies were conducted to examine the operating characteristics of the proposed study design.  The simulation studies show that the proposed Bayesian response-adaptive design identifies patients who benefit most from a targeted therapy and that there are substantial savings in the sample size requirements.
Topic revision: r2 - 26 Apr 2013, JohnBock

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