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Responder analyses and the assessment of a clinically relevant treatment effect

Ideally, a clinical trial should be able to demonstrate not only a statistically significant improvement in the primary efficacy endpoint, but also that the magnitude of the effect is clinically relevant. One proposed approach to address this question is a responder analysis, in which a continuous p...

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Detalles Bibliográficos
Autores principales: Snapinn, Steven M, Jiang, Qi
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2164942/
https://www.ncbi.nlm.nih.gov/pubmed/17961249
http://dx.doi.org/10.1186/1745-6215-8-31
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author Snapinn, Steven M
Jiang, Qi
author_facet Snapinn, Steven M
Jiang, Qi
author_sort Snapinn, Steven M
collection PubMed
description Ideally, a clinical trial should be able to demonstrate not only a statistically significant improvement in the primary efficacy endpoint, but also that the magnitude of the effect is clinically relevant. One proposed approach to address this question is a responder analysis, in which a continuous primary efficacy measure is dichotomized into "responders" and "non-responders." In this paper we discuss various weaknesses with this approach, including a potentially large cost in statistical efficiency, as well as its failure to achieve its main goal. We propose an approach in which the assessments of statistical significance and clinical relevance are separated.
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spelling pubmed-21649422008-01-02 Responder analyses and the assessment of a clinically relevant treatment effect Snapinn, Steven M Jiang, Qi Trials Methodology Ideally, a clinical trial should be able to demonstrate not only a statistically significant improvement in the primary efficacy endpoint, but also that the magnitude of the effect is clinically relevant. One proposed approach to address this question is a responder analysis, in which a continuous primary efficacy measure is dichotomized into "responders" and "non-responders." In this paper we discuss various weaknesses with this approach, including a potentially large cost in statistical efficiency, as well as its failure to achieve its main goal. We propose an approach in which the assessments of statistical significance and clinical relevance are separated. BioMed Central 2007-10-25 /pmc/articles/PMC2164942/ /pubmed/17961249 http://dx.doi.org/10.1186/1745-6215-8-31 Text en Copyright © 2007 Snapinn and Jiang; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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 Methodology
Snapinn, Steven M
Jiang, Qi
Responder analyses and the assessment of a clinically relevant treatment effect
title Responder analyses and the assessment of a clinically relevant treatment effect
title_full Responder analyses and the assessment of a clinically relevant treatment effect
title_fullStr Responder analyses and the assessment of a clinically relevant treatment effect
title_full_unstemmed Responder analyses and the assessment of a clinically relevant treatment effect
title_short Responder analyses and the assessment of a clinically relevant treatment effect
title_sort responder analyses and the assessment of a clinically relevant treatment effect
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2164942/
https://www.ncbi.nlm.nih.gov/pubmed/17961249
http://dx.doi.org/10.1186/1745-6215-8-31
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