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Activity Number:
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366
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #301950 |
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Title:
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Bayesian Dose-Finding in Oncology for Drug Combinations by Copula Regression
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Author(s):
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Ying Yuan*+
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Companies:
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The University of Texas M.D. Anderson Cancer Center
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Address:
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1515 Holcombe Blvd, Unit 447, Houston, TX, 77030,
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Keywords:
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Adaptive design ; Bayesian inference ; Combining drugs ; Continual reassessment
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Abstract:
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Treating patients with a combination of agents is becoming commonplace in cancer clinical trials, with biochemical synergism often the primary focus. In a typical drug combination trial, the toxicity profile of each individual drug has already been thoroughly studied in the single-agent trials, which naturally offers rich prior information. We propose a Bayesian adaptive design for dose-finding based on a copula-type model to account for the synergistic effect of two or more drugs in combination, while matching the toxicity profile of each single drug in the marginal model. To search for the maximum tolerated dose combination, we continuously update the posterior estimates for the toxicity probabilities of the combined doses. We conduct extensive simulation studies to examine the operating characteristics of the design.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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