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Activity Number: 701
Type: Contributed
Date/Time: Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract #316166
Title: Bayesian Dose-Finding Designs for Drug Combination Using the Times to Response-Toxicity Trade-Offs Assuming Partial Ordering
Author(s): Xiao Su* and Yisheng Li
Companies: The University of Texas Health Science Center and MD Anderson Cancer Center
Keywords: Adaptive design ; Bayesian design ; Dose-finding ; Utility ; Drug Combinations
Abstract:

Many phase I studies are designed to investigate combinations of two or more drugs. Determining the optimal dose for drug combinations to be administered remains a challenge because the dose-toxicity and dose-efficacy relationship may depend largely on unknown interactions. We models toxicity and efficacy as time-to-event outcomes using accelerated failure time (AFT) model. The dependency between the time to-toxicity and time-to-efficacy outcomes is adjusted by FGM copula model. Instead of the explicit dose-toxicity and dose-efficacy relationship, we only impose partial ordering assumptions on the acceleration factors corresponding to each dose-combination using Bayesian isotonic regression. A utility function is constructed based on trade-offs between the two time-to-event outcomes specified by the physicians.The new patients are allocated to the safe and efficacious combinations randomly proportional to the posterior median utility. The optimal combinations is selected as the combination maximizing posterior median utility The simulation studies suggest the proposed method has high probability to select the optimal dose-combinations.


Authors who are presenting talks have a * after their name.

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