Bayesian Hierarchical Modeling and Biomarker Cutoff Identification in Basket Trials

作者: Guosheng Yin , Zhao Yang , Motoi Odani , Satoru Fukimbara

DOI: 10.1080/19466315.2020.1811146

关键词:

摘要: Patients’ heterogeneity poses a fundamental problem in the rapidly developing field of precision medicine. Based on prespecified cutoff, biomarker-based designs provide flexible approach to sel...

参考文章(38)
Sumithra J. Mandrekar, Daniel J. Sargent, Drug designs fulfilling the requirements of clinical trials aiming at personalizing medicine Chinese clinical oncology. ,vol. 3, pp. 14- 14 ,(2014) , 10.3978/J.ISSN.2304-3865.2014.05.03
Scott M Berry, Kristine R Broglio, Susan Groshen, Donald A Berry, Bayesian hierarchical modeling of patient subpopulations: Efficient designs of Phase II oncology clinical trials: Clinical Trials. ,vol. 10, pp. 720- 734 ,(2013) , 10.1177/1740774513497539
J Jack Lee, Diane D Liu, A predictive probability design for phase II cancer clinical trials Clinical Trials. ,vol. 5, pp. 93- 106 ,(2008) , 10.1177/1740774508089279
Lorenzo Trippa, Yanxun Xu, Peter Müller, Yuan Ji, Yuan Ji, Subgroup-Based Adaptive (SUBA) Designs for Multi-Arm Biomarker Trials. Statistics in Biosciences. ,vol. 8, pp. 159- 180 ,(2016) , 10.1007/S12561-014-9117-1
Amanda J. Redig, Pasi A. Jänne, Basket Trials and the Evolution of Clinical Trial Design in an Era of Genomic Medicine Journal of Clinical Oncology. ,vol. 33, pp. 975- 977 ,(2015) , 10.1200/JCO.2014.59.8433
Boris Freidlin, Wenyu Jiang, Richard Simon, The Cross-Validated Adaptive Signature Design Clinical Cancer Research. ,vol. 16, pp. 691- 698 ,(2010) , 10.1158/1078-0432.CCR-09-1357
N. Simon, R. Simon, Adaptive enrichment designs for clinical trials Biostatistics. ,vol. 14, pp. 613- 625 ,(2013) , 10.1093/BIOSTATISTICS/KXT010
Lisa M. McShane, Sally Hunsberger, Alex A. Adjei, Effective Incorporation of Biomarkers into Phase II Trials Clinical Cancer Research. ,vol. 15, pp. 1898- 1905 ,(2009) , 10.1158/1078-0432.CCR-08-2033
W. Jiang, B. Freidlin, R. Simon, Biomarker-adaptive threshold design: a procedure for evaluating treatment with possible biomarker-defined subset effect. Journal of the National Cancer Institute. ,vol. 99, pp. 1036- 1043 ,(2007) , 10.1093/JNCI/DJM022