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New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs

Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of clinical trials while increasing their chance of success. But predictive biomarkers...

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Detalles Bibliográficos
Autores principales: Beckman, Robert A., Chen, Cong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sun Yat-sen University Cancer Center 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3845554/
https://www.ncbi.nlm.nih.gov/pubmed/23489587
http://dx.doi.org/10.5732/cjc.012.10248
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author Beckman, Robert A.
Chen, Cong
author_facet Beckman, Robert A.
Chen, Cong
author_sort Beckman, Robert A.
collection PubMed
description Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of clinical trials while increasing their chance of success. But predictive biomarkers do not always work. When unsuccessful, they add cost, complexity, and time to drug development. This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes. In the end, the biomarker is emphasized to the extent that it can actually predict.
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spelling pubmed-38455542013-12-11 New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs Beckman, Robert A. Chen, Cong Chin J Cancer Perspective Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of clinical trials while increasing their chance of success. But predictive biomarkers do not always work. When unsuccessful, they add cost, complexity, and time to drug development. This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes. In the end, the biomarker is emphasized to the extent that it can actually predict. Sun Yat-sen University Cancer Center 2013-05 /pmc/articles/PMC3845554/ /pubmed/23489587 http://dx.doi.org/10.5732/cjc.012.10248 Text en Chinese Journal of Cancer http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License, which allows readers to alter, transform, or build upon the article and then distribute the resulting work under the same or similar license to this one. The work must be attributed back to the original author and commercial use is not permitted without specific permission.
spellingShingle Perspective
Beckman, Robert A.
Chen, Cong
New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs
title New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs
title_full New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs
title_fullStr New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs
title_full_unstemmed New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs
title_short New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs
title_sort new evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3845554/
https://www.ncbi.nlm.nih.gov/pubmed/23489587
http://dx.doi.org/10.5732/cjc.012.10248
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