Advances in Clinical Trial Designs for Predictive Biomarker Discovery and Validation

被引:0
|
作者
Simon, Richard
机构
关键词
D O I
10.1007/s12609-009-0030-4
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Cancers of the same primary site are in many cases heterogeneous in molecular pathogenesis, clinical course, and treatment responsiveness. Current approaches for treatment development, evaluation, and use result in treatment of many patients with ineffective drugs and lead to the conduct of large clinical trials to identify small, average treatment benefits for heterogeneous groups of patients. New genomic and proteomic technologies provide powerful tools for the identification of patients who require systemic or aggressive treatment and the selection of those likely or unlikely to benefit from a specific regimen. In spite of the large literature on developing prognostic and predictive biomarkers and on statistical methodology for analysis of high dimensional data, there is considerable uncertainty about proper approaches for the validation of biomarker-based diagnostic tests. This article attempts to clarify these issues and provide a guide to recent publications on the design of clinical trials for evaluating the clinical utility and robustness of prognostic and predictive biomarkers.
引用
收藏
页码:216 / 221
页数:6
相关论文
共 50 条
  • [31] Protein biomarker discovery and validation: the long and uncertain path to clinical utility
    Rifai, Nader
    Gillette, Michael A.
    Carr, Steven A.
    NATURE BIOTECHNOLOGY, 2006, 24 (08) : 971 - 983
  • [32] Protein biomarker discovery and validation: the long and uncertain path to clinical utility
    Nader Rifai
    Michael A Gillette
    Steven A Carr
    Nature Biotechnology, 2006, 24 : 971 - 983
  • [33] Discovery and Validation of a Biomarker Model (PRESERVE) Predictive of Renal Outcomes After Liver Transplantation
    Levitsky, Josh
    Asrani, Sumeet K.
    Klintmalm, Goran
    Schiano, Thomas
    Moss, Adyr
    Chavin, Kenneth
    Miller, Charles
    Guo, Kexin
    Zhao, Lihui
    Jennings, Linda W.
    Brown, Merideth
    Armstrong, Brian
    Abecassis, Michael
    HEPATOLOGY, 2020, 71 (05) : 1775 - 1786
  • [34] LATEST ADVANCES IN BIOMARKER DISCOVERY AND DEVELOPMENT
    Tracy, M.
    DRUGS OF TODAY, 2012, 48 (11) : 735 - 739
  • [35] Metabolomics contribution to predictive biomarker discovery
    Cochereau, D.
    Junot, C.
    ONCOLOGIE, 2013, 15 (09) : 461 - 466
  • [36] A flexible approach for predictive biomarker discovery
    Boileau, Philippe
    Qi, Nina Ting
    van der Laan, Mark J.
    Dudoit, Sandrine
    Leng, Ning
    BIOSTATISTICS, 2023, 24 (04) : 1085 - 1105
  • [37] Clinical trial design for microarray predictive marker discovery and assessment
    Pusztai, L
    Hess, KR
    ANNALS OF ONCOLOGY, 2004, 15 (12) : 1731 - 1737
  • [38] Recent advances in LC-MS-based metabolomics for clinical biomarker discovery
    Chen, Chao-Jung
    Lee, Der-Yen
    Yu, Jiaxin
    Lin, Yu-Ning
    Lin, Tsung-Min
    MASS SPECTROMETRY REVIEWS, 2023, 42 (06) : 2349 - 2378
  • [39] Effect of Predictive Performance of a Biomarker for the Sample Size of Targeted Designs for Randomized Clinical Trials
    Lin, Xiwu
    Parks, Daniel C.
    Greshock, Joel
    Wooster, Richard
    Lee, Kwan R.
    STATISTICS IN BIOPHARMACEUTICAL RESEARCH, 2011, 3 (04): : 536 - 548
  • [40] Biomarker discovery and validation: the tide is turning
    Nice, Edouard
    EXPERT REVIEW OF PROTEOMICS, 2013, 10 (06) : 505 - 507