A Bayesian case study in oncology Phase I combination dose-finding using logistic regression with covariates

Abstract

A Bayesian approach to finding the maximum tolerated dose (MTD) is presented. The approach is flexible, allowing inclusion of covariates, and enables transparent dose recommendations based on comprehensive inferential summaries on the probability of dose-limiting toxicities (DLT). A case study is presented for a Phase I combination of two oncology drugs, nilotinib and imatinib. Data obtained and decisions made during the study are described. Final determination of the MTD pair is outlined, along with discussion regarding the use and interpretability of within- and end-of-study data.