Bayesian optimal interval designs for phase I clinical trials. Issue 3 (5th December 2014)

• Record Type: Journal Article
• Authors: Liu, Suyu; Yuan, Ying
• Is Part Of: Journal of the Royal Statistical Society. Volume 64:Issue 3(2015:May)
• Page Start: 507
• Page End: 523
• Publication Date: 2014-12-05
• Subjects: Statistics -- Periodicals; 519.5
• DOI: 10.1111/rssc.12089
• Languages: English
• ISSNs: 0035-9254

Abstract

<abstract abstract-type="main" id="rssc12089-abs-0001"> <title>Summary</title> <p>In phase I trials, effectively treating patients and minimizing the chance of exposing them to subtherapeutic and overly toxic doses are clinicians' top priority. Motived by this practical consideration, we propose Bayesian optimal interval (BOIN) designs to find the maximum tolerated dose and to minimize the probability of inappropriate dose assignments for patients. We show, both theoretically and numerically, that the BOIN design not only has superior finite and large sample properties but also can be easily implemented in a simple way similar to the traditional '3+3' design. Compared with the well‐known continual reassessment method, the BOIN design yields comparable average performance to select the maximum tolerated dose but has a substantially lower risk of assigning patients to subtherapeutic and overly toxic doses. We apply the BOIN design to two cancer clinical trials.</p> </abstract>