A dose–schedule finding design for phase I–II clinical trials. Issue 2 (10th August 2015)

• Record Type: Journal Article
• Authors: Guo, Beibei; Li, Yisheng; Yuan, Ying
• Is Part Of: Journal of the Royal Statistical Society. Volume 65:Issue 2(2016:Mar.)
• Page Start: 259
• Page End: 272
• Publication Date: 2015-08-10
• Subjects: Bayesian dynamic model -- Dose–schedule combination -- Efficacy -- Probit model -- Schedule–response relationship -- Toxicity; Statistics -- Periodicals; 519.5
• DOI: 10.1111/rssc.12113
• Languages: English
• ISSNs: 0035-9254

Abstract

Summary: Dose finding methods aiming at identifying an optimal dose of a treatment with a given schedule may be at a risk of misidentifying the best treatment for patients. We propose a phase I–II clinical trial design to find the optimal dose–schedule combination. We define schedule as the method and timing of administration of a given total dose in a treatment cycle. We propose a Bayesian dynamic model for the joint effects of dose and schedule. The model proposed allows us to borrow strength across dose–schedule combinations without making overly restrictive assumptions on the ordering pattern of the schedule effects. We develop a dose–schedule finding algorithm to allocate patients sequentially to a desirable dose–schedule combination, and to select an optimal combination at the end of the trial. We apply the proposed design to a phase I–II clinical trial of a γ ‐secretase inhibitor in patients with refractory metastatic or locally advanced solid tumours, and we examine the operating characteristics of the design through simulations.