A Bayesian dose finding design for dual endpoint phase I trials.
We propose a dose-finding weighted design for an early clinical trial which aims to determine the optimal dose, selected on the basis of both efficacy and toxicity, to be used in patients entering subsequent studies in a drug development process. The goal is to identify the optimal dose, while using a minimal number of subjects. For each dose under test, a decision table is defined with a utility value attached to each possible decision. The relationship between the utility and the target probability for each outcome is shown. A Dirichlet prior is used and we illustrate the process of maximizing the expected utility under the resulting posterior distribution to find the optimal decision at each stage of the trial. We show how this affects the eventual choice of optimal dose in various scenarios. Properties of our design are discussed and compared with a current standard design.
Loke
Yee-Chong
YC
Divison of Clinical Trials & Epidemiological Sciences, National Cancer Centre Singapore, 11 Hospital Drive, Singapore 169610, Singapore.
Tan
Say-Beng
SB
Cai
YiYu
Y
Machin
David
D
D019380:Anti-HIV Agents / Q000008:administration & dosage; D001499:Bayes Theorem; D002648:Child; D017321:Clinical Trials, Phase I as Topic / Q000379:methods*; D003198:Computer Simulation; D015658:HIV Infections / Q000188:drug therapy; D006801:Humans; D020714:Maximum Tolerated Dose; D012107:Research Design; D019562:Viral Load
D019380:Anti-HIV Agents