A robust Bayesian dose-finding design for phase I/II clinical trials.
We propose a Bayesian phase I/II dose-finding trial design that simultaneously accounts for toxicity and efficacy. We model the toxicity and efficacy of investigational doses using a flexible Bayesian dynamic model, which borrows information across doses without imposing stringent parametric assumptions on the shape of the dose-toxicity and dose-efficacy curves. An intuitive utility function that reflects the desirability trade-offs between efficacy and toxicity is used to guide the dose assignment and selection. We also discuss the extension of this design to handle delayed toxicity and efficacy. We conduct extensive simulation studies to examine the operating characteristics of the proposed method under various practical scenarios. The results show that the proposed design possesses good operating characteristics and is robust to the shape of the dose-toxicity and dose-efficacy curves.
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA syliu@mdanderson.org.
Suyu
S
Liu
Department of Statistics, Texas A&M University, College Station, TX, USA.
Valen E
VE
Johnson
D001499:Bayes Theorem; D017321:Clinical Trials, Phase I as Topic; D017322:Clinical Trials, Phase II as Topic; D004305:Dose-Response Relationship, Drug; D006801:Humans; D012107:Research Design
Adaptive design; Bayesian method; Phase I/II trial; Trade-off; Utility