Decision-theoretic designs for dose-finding clinical trials with multiple outcomes

Fan, Shenghau K. & Wang, You-Gan (2006) Decision-theoretic designs for dose-finding clinical trials with multiple outcomes. Statistics in Medicine, 25(10), pp. 1699-1714.

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Abstract

A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.

Impact and interest:

3 citations in Scopus
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3 citations in Web of Science®

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ID Code: 90520
Item Type: Journal Article
Refereed: Yes
Keywords: bandit process, optimality, sequential clinical trials, sub-optimality, continual reassessment method, efficacy, oncology, safety
DOI: 10.1002/sim.2322
ISSN: 0277-6715
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 18 Nov 2015 01:20
Last Modified: 18 Nov 2015 01:20

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