A dose-finding design for phase I clinical trials based on Bayesian stochastic approximation

被引：0
作者：
Jin Xu
Dapeng Zhang
Rongji Mu
机构：
[1] School of Statistics,
[2] East China Normal University,undefined
[3] Key Laboratory of Advanced Theory and Application in Statistics and Data Science - MOE,undefined
[4] East China Normal University,undefined
[5] Clinical Research Center,undefined
[6] Shanghai Jiao Tong University School of Medicine,undefined
来源：
BMC Medical Research Methodology | / 22卷
关键词：
Adaptive design; Dose-finding; Maximum tolerated dose; Stochastic approximation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 71 条
[11]  
O’Quigley J(2017)Keyboard: a novel Bayesian toxicity probability interval design for phase I clinical trials Clin Cancer Res. 23 3994-4003
[12]  
Pepe M(2015)Bayesian optimal interval designs for phase I clinical trials J R Stat Soc Ser C. 64 507-23
[13]  
Fisher L(2016)Bayesian optimal interval design: A simple and well-performing design for phase I oncology trials Clin Cancer Res. 22 4291-301
[14]  
Babb J(1951)A Stochastic Approximation Method Ann Math Stat. 22 400-7
[15]  
Rogatko A(2003)Stochastic approximation Ann Stat. 31 391-406
[16]  
Zacks S(2004)Efficient Robbins-Monro procedure for binary data Biometrika. 91 461-70
[17]  
Tighiouart M(2010)Stochastic approximation and modern model based designs for dose-finding clinical trials Stat Sci. 25 191-201
[18]  
Rogatko A(2021)A Bayesian stochastic approximation method J Stat Plan Infer. 211 391-401
[19]  
Neuenschwander B(2005)Coherence principles in dose-finding studies Biometrika. 92 863-73
[20]  
Branson M(2011)Dose-finding designs: the role of convergence properties Int J Biostat. 7 39-47
12345678