372 – Contributed Oral Poster Presentations: Biopharmaceutical Section
Dose-Finding for Drug Combination in Early Cancer Phase I Trials Using Conditional Continual Reassessment Method
Mourad Tighiouart
Cedars Sinai Medical Center
Quanlin Li
Cedars Sinai Medical Center
We present a Bayesian adaptive design 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 for continuous dose levels of the two agents. Parametric models are used to describe the relationship between the doses and the probability of dose limiting toxicity (DLT). Trial design proceeds using the continual reassessment method, where at each stage of the trial, we seek the dose of one agent with estimated probability of DLT closest to a target probability of DLT given the current dose of the other agent. At the end of the trial, we estimate the MTD curve as a function of Bayes estimates of the model parameters. We evaluate design operating characteristics in terms of safety of the trial and percent of dose recommendation at dose combination neighborhoods around the true MTD. The method is further adapted to the case of a pre-specified discrete set of dose combinations and we show how more than one dose combination can be recommended as the MTD. We also examine the performance of the approach under model misspecifications for the true dose-toxicity relationship.