title: A hybrid Bayesian adaptive design for dose response trials.
abstract: 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.
authors: Millennium Pharmaceuticals, Inc., Cambridge, Massachusetts, USA. mark.chang@mpi.com
authors: Mark
authors: M
authors: Chang
authors: Shein-Chung
authors: SC
authors: Chow
mesh_terms: 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*
chemical_list: D000970:Antineoplastic Agents