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The number needed to treat and relevant between-trial comparisons of competing interventions
The number needed to treat (NNT) is considered an intuitive as well as popular effect measure. The aims of this review were to 1) explain why we cannot compare trial-specific NNT estimates for the competing treatments evaluated in different randomized controlled trials (RCTs) and 2) outline the prin...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298880/ https://www.ncbi.nlm.nih.gov/pubmed/30588048 http://dx.doi.org/10.2147/CEOR.S180491 |
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author | Jansen, Jeroen P Khalid, Javaria Mona Smyth, Michael D Patel, Haridarshan |
author_facet | Jansen, Jeroen P Khalid, Javaria Mona Smyth, Michael D Patel, Haridarshan |
author_sort | Jansen, Jeroen P |
collection | PubMed |
description | The number needed to treat (NNT) is considered an intuitive as well as popular effect measure. The aims of this review were to 1) explain why we cannot compare trial-specific NNT estimates for the competing treatments evaluated in different randomized controlled trials (RCTs) and 2) outline the principles of how relative treatment effects of different trials can be compared and results can be presented as NNT, without violating the principles of valid between-trial comparisons. Our premise is that ratio measures for relative treatment effects of response outcomes are less prone to effect modification than absolute difference measures of response outcomes. Accordingly, any between-trial comparisons of the efficacy of competing interventions using the study-specific ORs are less likely to be invalid or biased than comparisons based on the study-specific NNT estimates. However, treatment-specific ORs obtained from a meta-analysis or taken directly from an individual study can be transformed into consistent treatment-specific NNT estimates that allow for credible comparisons of treatments when these ratio measures are applied to the same reference response estimate. The theoretical discussion is illustrated with a relevant indirect comparison of biologics for the treatment of ulcerative colitis. Between-trial comparisons directly based on the NNT of individual trials may result in erroneous conclusions and should be avoided. Treatment-specific NNT estimates need to be based on the same probability of response with the common reference treatment against which the interventions are compared. |
format | Online Article Text |
id | pubmed-6298880 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-62988802018-12-26 The number needed to treat and relevant between-trial comparisons of competing interventions Jansen, Jeroen P Khalid, Javaria Mona Smyth, Michael D Patel, Haridarshan Clinicoecon Outcomes Res Review The number needed to treat (NNT) is considered an intuitive as well as popular effect measure. The aims of this review were to 1) explain why we cannot compare trial-specific NNT estimates for the competing treatments evaluated in different randomized controlled trials (RCTs) and 2) outline the principles of how relative treatment effects of different trials can be compared and results can be presented as NNT, without violating the principles of valid between-trial comparisons. Our premise is that ratio measures for relative treatment effects of response outcomes are less prone to effect modification than absolute difference measures of response outcomes. Accordingly, any between-trial comparisons of the efficacy of competing interventions using the study-specific ORs are less likely to be invalid or biased than comparisons based on the study-specific NNT estimates. However, treatment-specific ORs obtained from a meta-analysis or taken directly from an individual study can be transformed into consistent treatment-specific NNT estimates that allow for credible comparisons of treatments when these ratio measures are applied to the same reference response estimate. The theoretical discussion is illustrated with a relevant indirect comparison of biologics for the treatment of ulcerative colitis. Between-trial comparisons directly based on the NNT of individual trials may result in erroneous conclusions and should be avoided. Treatment-specific NNT estimates need to be based on the same probability of response with the common reference treatment against which the interventions are compared. Dove Medical Press 2018-12-14 /pmc/articles/PMC6298880/ /pubmed/30588048 http://dx.doi.org/10.2147/CEOR.S180491 Text en © 2018 Jansen et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Review Jansen, Jeroen P Khalid, Javaria Mona Smyth, Michael D Patel, Haridarshan The number needed to treat and relevant between-trial comparisons of competing interventions |
title | The number needed to treat and relevant between-trial comparisons of competing interventions |
title_full | The number needed to treat and relevant between-trial comparisons of competing interventions |
title_fullStr | The number needed to treat and relevant between-trial comparisons of competing interventions |
title_full_unstemmed | The number needed to treat and relevant between-trial comparisons of competing interventions |
title_short | The number needed to treat and relevant between-trial comparisons of competing interventions |
title_sort | number needed to treat and relevant between-trial comparisons of competing interventions |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298880/ https://www.ncbi.nlm.nih.gov/pubmed/30588048 http://dx.doi.org/10.2147/CEOR.S180491 |
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