title: A dose-schedule finding design for phase I-II clinical trials.
abstract: 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. In this article 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 proposed model 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 sequentially allocate patients to a desirable dose-schedule combination, and select an optimal combination at the end of the trial. We apply the proposed design to a phase I/II clinical trial of aγ-secretase inhibitor in patients with refractory metastatic or locally advanced solid tumours, and examine the operating characteristics of the design through simulations.
authors.affiliation: Department of Experimental Statistics, Louisiana State University Baton Rouge, LA 70803, USA.
authors.forename: Beibei
authors.initials: B
authors.lastname: Guo
authors.affiliation: Department of Biostatistics, The University of Texas MD Anderson Cancer Center Houston, TX 77030, USA.
authors.forename: Yisheng
authors.initials: Y
authors.lastname: Li
authors.affiliation: Department of Biostatistics, The University of Texas MD Anderson Cancer Center Houston, TX 77030, USA.
authors.forename: Ying
authors.initials: Y
authors.lastname: Yuan
keywords: Bayesian dynamic model; dose-schedule combination; efficacy; probit model; schedule-response relationship; toxicity