Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration

BMC Medicine

Correspondence

Richard M Simon¹  Lisa M McShane²  Mei-Yin C Polley³  James V Tricoli⁴  Tracy G Lively⁵  Barbara A Conley⁶  Kelly Y Kim⁷  Margaret M Cavenagh⁸  Jill P Mesirov⁹  Jeremy MG Taylor^1,10  David A Eberhard^1,11  William L Bigbee^1,12  P Mickey Williams^1,13  James H Doroshow^1,14  Deborah J Shuman^1,14 

[1] Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Room 5W110, 9609 Medical Center Drive, 20892, Bethesda, MD, USA;Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Room 5W130, MSC 9735, 9609 Medical Center Drive, 20892-9735, Bethesda, MD, USA;Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Room 5W638, 9609 Medical Center Drive, 20892, Bethesda, MD, USA;Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Room 3W526, 9609 Medical Center Drive, 20892, Bethesda, MD, USA;Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Room 4W420, MSC 9730, 9609 Medical Center Drive, 20892, Bethesda, MD, USA;Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Room 4W426, 9609 Medical Center Drive, 20892, Bethesda, MD, USA;Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Room 4W430, 9609 Medical Center Drive, 20892, Bethesda, MD, USA;Cancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Room 4W432, MSC 9730, 9609 Medical Center Drive, 20892, Bethesda, MD, USA;Computational Biology and Bioinformatics, Broad Institute of Massachusetts Institute of Technology and Harvard University, 7 Cambridge Center, 02142, Cambridge, MA, USA;Department of Biostatistics, University of Michigan, 1415 Washington Heights, 48109, Ann Arbor, MI, USA;Department of Pathology and Lineberger Comprehensive Cancer Center, University of North Carolina, Campus Box 7525, Brinkhous-Bullitt Bldg., 27599, Chapel Hill, NC, USA;Department of Pathology, and University of Pittsburgh Cancer Institute, Hillman Cancer Center, UPCI Research Pavilion, Suite 2.32b, 5117 Centre Avenue, 15213, Pittsburgh, PA, USA;Frederick National Laboratory for Cancer Research, National Cancer Institute, National Institutes of Health, Bldg. 320, Room 2, 1050 Boyles Street, 21702, Frederick, MD, USA;Office of the Director, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Room 3A44, 31 Center Drive, 20892, Bethesda, MD, USA;

关键词: Analytical validation;    Biomarker;    Diagnostic test;    Genomic classifier;    Model validation;    Molecular profile;    Omics;    Personalized medicine;    Precision Medicine;    Treatment selection;   

DOI  :  10.1186/1741-7015-11-220

 received in 2013-05-28, accepted in 2013-08-06,  发布年份 2013

来源: Springer

【 摘 要 】

High-throughput ‘omics’ technologies that generate molecular profiles for biospecimens have been extensively used in preclinical studies to reveal molecular subtypes and elucidate the biological mechanisms of disease, and in retrospective studies on clinical specimens to develop mathematical models to predict clinical endpoints. Nevertheless, the translation of these technologies into clinical tests that are useful for guiding management decisions for patients has been relatively slow. It can be difficult to determine when the body of evidence for an omics-based test is sufficiently comprehensive and reliable to support claims that it is ready for clinical use, or even that it is ready for definitive evaluation in a clinical trial in which it may be used to direct patient therapy. Reasons for this difficulty include the exploratory and retrospective nature of many of these studies, the complexity of these assays and their application to clinical specimens, and the many potential pitfalls inherent in the development of mathematical predictor models from the very high-dimensional data generated by these omics technologies. Here we present a checklist of criteria to consider when evaluating the body of evidence supporting the clinical use of a predictor to guide patient therapy. Included are issues pertaining to specimen and assay requirements, the soundness of the process for developing predictor models, expectations regarding clinical study design and conduct, and attention to regulatory, ethical, and legal issues. The proposed checklist should serve as a useful guide to investigators preparing proposals for studies involving the use of omics-based tests. The US National Cancer Institute plans to refer to these guidelines for review of proposals for studies involving omics tests, and it is hoped that other sponsors will adopt the checklist as well.

【 授权许可】

CC BY   
© McShane et al.; licensee BioMed Central Ltd. 2013