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A dose–schedule finding design for phase I–II clinical trials
Author(s) -
Guo Beibei,
Li Yisheng,
Yuan Ying
Publication year - 2016
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12113
Subject(s) - schedule , phase (matter) , clinical trial , reliability engineering , medicine , computer science , engineering , chemistry , operating system , organic chemistry
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.