293 – Dose Finding, Dose Range, and Oncology Trials
Dose Finding for Drug Combination in Early Cancer Phase I Trials Using Conditional Escalation with Overdose Control
Mourad Tighiouart
Cedars Sinai Medical Center
André Rogatko
Samuel Oschin Comprehensive Cancer Institute at Cedars-Sinai Medical Center
Steven Piantadosi
Cedars-Sinai Medical Center
We present Bayesian adaptive designs for dose finding of a combination of two drugs in cancer phase I clinical trials. The goal is to estimate the maximum tolerated dose (MTD) as a curve in the two-dimensional Cartesian plane. Parametric models are used to describe the relationship between the doses of the two agents and the probability of dose limiting toxicity. We investigate different reparametrizations in terms of parameters clinicians can easily interpret. Trial design proceeds using univariate escalation with overdose control, where at each stage of the trial, we seek a dose of one agent using the current posterior distribution of the MTD of this agent given the current dose of the other agent. At the end of the trial, an estimate of the MTD curve is proposed as a function of Bayes estimates of the model parameters. We evaluate design operating characteristics in terms of safety of the trial design and percent of dose recommendation at dose combination neighborhoods around the true MTD curve. We also examine the performance of the approach under model misspecifications for the true dose-toxicity relationship.