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Activity Number: 315 - Innovative Bayesian Approaches in Clinical Trials and Practical Considerations
Type: Invited
Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #300258 Presentation
Title: Design of Drug Combination Early Phase Cancer Trials Under the Setting of Partial Toxicity Attribution
Author(s): Mourad Tighiouart*
Companies: Cedars-Sinai Medical Center
Keywords: Attributable toxicity; cancer phase I/II trials; continual reassessment method; copula type models; drug combination; Cubic splines

In this talk, I present a Bayesian adaptive design for drug combination early phase cancer clinical trials when a fraction of dose limiting toxicities is attributable to one or both drugs. Copula regression models are used to describe the dose toxicity relationship. The dose escalation algorithm uses cohorts of two patients, following the continual reassessment method scheme, where at each stage of the trial, we search for the dose of one agent given the current dose of the other agent. At the end of the trial, the maximum tolerated dose (MTD) curve is estimated as a function of model parameters in the setting of continuous dose levels. An outcome adaptive design is then carried out in a phase II trial with the goal of determining dose combinations along the MTD curve that achieve maximal treatment efficacy. The methodology is illustrated by extensive simulations and application to a real trial. We show that the design is safe under a large number of practical scenarios and the optimal dose estimated with high precision.

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

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