A Bayesian Adaptive Design for Cancer Phase I Trials Using a Flexible Range of Doses

• Activity Number: 350
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Galen Cook-Wiens*+ and Mourad Tighiouart and Andre Rogatko
• Companies: Cedars-Sinai Medical Center and Cedars-Sinai Medical Center and Cedars-Sinai Medical Center
• Keywords: Cancer Phase I trials ; Maximum tolerated dose ; Escalation With Overdose Control ; Dose limiting toxicity ; Continuous dose ; Flexible dose range

Abstract

We present a Bayesian adaptive design for dose finding in cancer phase I clinical trials. The goal is to estimate the maximum tolerated dose (MTD) after possible modification of the dose range during the trial. Parametric models are used to describe the relationship between the dose and the probability of dose limiting toxicity (DLT). We investigate model reparameterization in terms of the probabilities of DLT at the minimum and maximum available doses at the start of the trial. Trial design proceeds using escalation with overdose control (EWOC), where at each stage of the trial, we seek the dose of the agent such that the posterior probability of exceeding the MTD of this agent is bounded by a feasibility bound. At any time during the trial, we test whether the MTD is below or above the minimum and maximum doses, respectively. If during the trial, there is evidence that the MTD is outside the range of doses, we extend the range of doses and complete the trial with the planned sample size. At the end of the trial, a Bayes estimate of the MTD is proposed. We evaluate design operating characteristics in terms of safety of the trial design and efficiency of the MTD estimate. The methodology is further compared to the original EWOC design.