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

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...

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Autores principales: McShane, Lisa M, Cavenagh, Margaret M, Lively, Tracy G, Eberhard, David A, Bigbee, William L, Williams, P Mickey, Mesirov, Jill P, Polley, Mei-Yin C, Kim, Kelly Y, Tricoli, James V, Taylor, Jeremy MG, Shuman, Deborah J, Simon, Richard M, Doroshow, James H, Conley, Barbara A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852338/
https://www.ncbi.nlm.nih.gov/pubmed/24228635
http://dx.doi.org/10.1186/1741-7015-11-220
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author McShane, Lisa M
Cavenagh, Margaret M
Lively, Tracy G
Eberhard, David A
Bigbee, William L
Williams, P Mickey
Mesirov, Jill P
Polley, Mei-Yin C
Kim, Kelly Y
Tricoli, James V
Taylor, Jeremy MG
Shuman, Deborah J
Simon, Richard M
Doroshow, James H
Conley, Barbara A
author_facet McShane, Lisa M
Cavenagh, Margaret M
Lively, Tracy G
Eberhard, David A
Bigbee, William L
Williams, P Mickey
Mesirov, Jill P
Polley, Mei-Yin C
Kim, Kelly Y
Tricoli, James V
Taylor, Jeremy MG
Shuman, Deborah J
Simon, Richard M
Doroshow, James H
Conley, Barbara A
author_sort McShane, Lisa M
collection PubMed
description 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.
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spelling pubmed-38523382013-12-19 Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration McShane, Lisa M Cavenagh, Margaret M Lively, Tracy G Eberhard, David A Bigbee, William L Williams, P Mickey Mesirov, Jill P Polley, Mei-Yin C Kim, Kelly Y Tricoli, James V Taylor, Jeremy MG Shuman, Deborah J Simon, Richard M Doroshow, James H Conley, Barbara A BMC Med Correspondence 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. BioMed Central 2013-10-17 /pmc/articles/PMC3852338/ /pubmed/24228635 http://dx.doi.org/10.1186/1741-7015-11-220 Text en Copyright © 2013 McShane et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Correspondence
McShane, Lisa M
Cavenagh, Margaret M
Lively, Tracy G
Eberhard, David A
Bigbee, William L
Williams, P Mickey
Mesirov, Jill P
Polley, Mei-Yin C
Kim, Kelly Y
Tricoli, James V
Taylor, Jeremy MG
Shuman, Deborah J
Simon, Richard M
Doroshow, James H
Conley, Barbara A
Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration
title Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration
title_full Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration
title_fullStr Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration
title_full_unstemmed Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration
title_short Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration
title_sort criteria for the use of omics-based predictors in clinical trials: explanation and elaboration
topic Correspondence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852338/
https://www.ncbi.nlm.nih.gov/pubmed/24228635
http://dx.doi.org/10.1186/1741-7015-11-220
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