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Extensions of the probabilistic ranking metrics of competing treatments in network meta‐analysis to reflect clinically important relative differences on many outcomes
One of the key features of network meta‐analysis is ranking of interventions according to outcomes of interest. Ranking metrics are prone to misinterpretation because of two limitations associated with the current ranking methods. First, differences in relative treatment effects might not be clinica...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078966/ https://www.ncbi.nlm.nih.gov/pubmed/31661561 http://dx.doi.org/10.1002/bimj.201900026 |
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author | Mavridis, Dimitris Porcher, Raphaël Nikolakopoulou, Adriani Salanti, Georgia Ravaud, Philippe |
author_facet | Mavridis, Dimitris Porcher, Raphaël Nikolakopoulou, Adriani Salanti, Georgia Ravaud, Philippe |
author_sort | Mavridis, Dimitris |
collection | PubMed |
description | One of the key features of network meta‐analysis is ranking of interventions according to outcomes of interest. Ranking metrics are prone to misinterpretation because of two limitations associated with the current ranking methods. First, differences in relative treatment effects might not be clinically important and this is not reflected in the ranking metrics. Second, there are no established methods to include several health outcomes in the ranking assessments. To address these two issues, we extended the P‐score method to allow for multiple outcomes and modified it to measure the mean extent of certainty that a treatment is better than the competing treatments by a certain amount, for example, the minimum clinical important difference. We suggest to present the tradeoff between beneficial and harmful outcomes allowing stakeholders to consider how much adverse effect they are willing to tolerate for specific gains in efficacy. We used a published network of 212 trials comparing 15 antipsychotics and placebo using a random effects network meta‐analysis model, focusing on three outcomes; reduction in symptoms of schizophrenia in a standardized scale, all‐cause discontinuation, and weight gain. |
format | Online Article Text |
id | pubmed-7078966 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-70789662020-03-19 Extensions of the probabilistic ranking metrics of competing treatments in network meta‐analysis to reflect clinically important relative differences on many outcomes Mavridis, Dimitris Porcher, Raphaël Nikolakopoulou, Adriani Salanti, Georgia Ravaud, Philippe Biom J Research Papers One of the key features of network meta‐analysis is ranking of interventions according to outcomes of interest. Ranking metrics are prone to misinterpretation because of two limitations associated with the current ranking methods. First, differences in relative treatment effects might not be clinically important and this is not reflected in the ranking metrics. Second, there are no established methods to include several health outcomes in the ranking assessments. To address these two issues, we extended the P‐score method to allow for multiple outcomes and modified it to measure the mean extent of certainty that a treatment is better than the competing treatments by a certain amount, for example, the minimum clinical important difference. We suggest to present the tradeoff between beneficial and harmful outcomes allowing stakeholders to consider how much adverse effect they are willing to tolerate for specific gains in efficacy. We used a published network of 212 trials comparing 15 antipsychotics and placebo using a random effects network meta‐analysis model, focusing on three outcomes; reduction in symptoms of schizophrenia in a standardized scale, all‐cause discontinuation, and weight gain. John Wiley and Sons Inc. 2019-10-29 2020-03 /pmc/articles/PMC7078966/ /pubmed/31661561 http://dx.doi.org/10.1002/bimj.201900026 Text en © 2019 The Authors. Biometrical Journal published by WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Papers Mavridis, Dimitris Porcher, Raphaël Nikolakopoulou, Adriani Salanti, Georgia Ravaud, Philippe Extensions of the probabilistic ranking metrics of competing treatments in network meta‐analysis to reflect clinically important relative differences on many outcomes |
title | Extensions of the probabilistic ranking metrics of competing treatments in network meta‐analysis to reflect clinically important relative differences on many outcomes |
title_full | Extensions of the probabilistic ranking metrics of competing treatments in network meta‐analysis to reflect clinically important relative differences on many outcomes |
title_fullStr | Extensions of the probabilistic ranking metrics of competing treatments in network meta‐analysis to reflect clinically important relative differences on many outcomes |
title_full_unstemmed | Extensions of the probabilistic ranking metrics of competing treatments in network meta‐analysis to reflect clinically important relative differences on many outcomes |
title_short | Extensions of the probabilistic ranking metrics of competing treatments in network meta‐analysis to reflect clinically important relative differences on many outcomes |
title_sort | extensions of the probabilistic ranking metrics of competing treatments in network meta‐analysis to reflect clinically important relative differences on many outcomes |
topic | Research Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7078966/ https://www.ncbi.nlm.nih.gov/pubmed/31661561 http://dx.doi.org/10.1002/bimj.201900026 |
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