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Quantitative benefit–harm assessment for setting research priorities: the example of roflumilast for patients with COPD

BACKGROUND: When faced with uncertainties about the effects of medical interventions regulatory agencies, guideline developers, clinicians, and researchers commonly ask for more research, and in particular for more randomized trials. The conduct of additional randomized trials is, however, sometimes...

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Detalles Bibliográficos
Autores principales: Puhan, Milo A., Yu, Tsung, Boyd, Cynthia M., ter Riet, Gerben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4490602/
https://www.ncbi.nlm.nih.gov/pubmed/26137986
http://dx.doi.org/10.1186/s12916-015-0398-0
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author Puhan, Milo A.
Yu, Tsung
Boyd, Cynthia M.
ter Riet, Gerben
author_facet Puhan, Milo A.
Yu, Tsung
Boyd, Cynthia M.
ter Riet, Gerben
author_sort Puhan, Milo A.
collection PubMed
description BACKGROUND: When faced with uncertainties about the effects of medical interventions regulatory agencies, guideline developers, clinicians, and researchers commonly ask for more research, and in particular for more randomized trials. The conduct of additional randomized trials is, however, sometimes not the most efficient way to reduce uncertainty. Instead, approaches such as value of information analysis or other approaches should be used to prioritize research that will most likely reduce uncertainty and inform decisions. DISCUSSION: In situations where additional research for specific interventions needs to be prioritized, we propose the use of quantitative benefit–harm assessments that illustrate how the benefit–harm balance may change as a consequence of additional research. The example of roflumilast for patients with chronic obstructive pulmonary disease shows that additional research on patient preferences (e.g., how important are exacerbations relative to psychiatric harms?) or outcome risks (e.g., what is the incidence of psychiatric outcomes in patients with chronic obstructive pulmonary disease without treatment?) is sometimes more valuable than additional randomized trials. SUMMARY: We propose that quantitative benefit–harm assessments have the potential to explore the impact of additional research and to identify research priorities Our approach may be seen as another type of value of information analysis and as a useful approach to stimulate specific new research that has the potential to change current estimates of the benefit–harm balance and decision making.
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spelling pubmed-44906022015-07-04 Quantitative benefit–harm assessment for setting research priorities: the example of roflumilast for patients with COPD Puhan, Milo A. Yu, Tsung Boyd, Cynthia M. ter Riet, Gerben BMC Med Opinion BACKGROUND: When faced with uncertainties about the effects of medical interventions regulatory agencies, guideline developers, clinicians, and researchers commonly ask for more research, and in particular for more randomized trials. The conduct of additional randomized trials is, however, sometimes not the most efficient way to reduce uncertainty. Instead, approaches such as value of information analysis or other approaches should be used to prioritize research that will most likely reduce uncertainty and inform decisions. DISCUSSION: In situations where additional research for specific interventions needs to be prioritized, we propose the use of quantitative benefit–harm assessments that illustrate how the benefit–harm balance may change as a consequence of additional research. The example of roflumilast for patients with chronic obstructive pulmonary disease shows that additional research on patient preferences (e.g., how important are exacerbations relative to psychiatric harms?) or outcome risks (e.g., what is the incidence of psychiatric outcomes in patients with chronic obstructive pulmonary disease without treatment?) is sometimes more valuable than additional randomized trials. SUMMARY: We propose that quantitative benefit–harm assessments have the potential to explore the impact of additional research and to identify research priorities Our approach may be seen as another type of value of information analysis and as a useful approach to stimulate specific new research that has the potential to change current estimates of the benefit–harm balance and decision making. BioMed Central 2015-07-02 /pmc/articles/PMC4490602/ /pubmed/26137986 http://dx.doi.org/10.1186/s12916-015-0398-0 Text en © Puhan et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Opinion
Puhan, Milo A.
Yu, Tsung
Boyd, Cynthia M.
ter Riet, Gerben
Quantitative benefit–harm assessment for setting research priorities: the example of roflumilast for patients with COPD
title Quantitative benefit–harm assessment for setting research priorities: the example of roflumilast for patients with COPD
title_full Quantitative benefit–harm assessment for setting research priorities: the example of roflumilast for patients with COPD
title_fullStr Quantitative benefit–harm assessment for setting research priorities: the example of roflumilast for patients with COPD
title_full_unstemmed Quantitative benefit–harm assessment for setting research priorities: the example of roflumilast for patients with COPD
title_short Quantitative benefit–harm assessment for setting research priorities: the example of roflumilast for patients with COPD
title_sort quantitative benefit–harm assessment for setting research priorities: the example of roflumilast for patients with copd
topic Opinion
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4490602/
https://www.ncbi.nlm.nih.gov/pubmed/26137986
http://dx.doi.org/10.1186/s12916-015-0398-0
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