A hybrid Bayesian adaptive design for dose response trials.
In recent years, the use of adaptive design methods based on accrued data of on-going trials have become very popular for dose response trials in early clinical development due to their flexibility (EMEA, 2002). In this paper, we developed a hybrid frequentist-Bayesian continual reassessment method (CRM) in conjunction with utility-adaptive randomization for clinical trial designs with multiple endpoints. The proposed hyperlogistic function family with multiple parameters gives users flexibility for probability modeling. CRM reassesses a dose-response relationship based on accrued data of the on-going trial, which allows investigators to make decisions based on a constantly updated dose-response model. The proposed utility-adaptive randomization for multiple-endpoint trials allows more patients to be assigned to superior treatment groups. The performance of the proposed method was examined in terms of its operating characteristics through computer simulations.
Chang
Mark
M
Millennium Pharmaceuticals, Inc., Cambridge, Massachusetts, USA. mark.chang@mpi.com
Chow
Shein-Chung
SC
D000465:Algorithms; D000970:Antineoplastic Agents / Q000009:adverse effects / Q000627:therapeutic use; D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D017321:Clinical Trials, Phase I as Topic; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D023381:Endpoint Determination; D016013:Likelihood Functions; D015233:Models, Statistical; D011897:Random Allocation; D012107:Research Design / Q000706:statistics & numerical data*
D000970:Antineoplastic Agents