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Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis

BACKGROUND: The relative treatment effects estimated from network meta-analysis can be employed to rank treatments from the most preferable to the least preferable option. These treatment hierarchies are typically based on ranking metrics calculated from a single outcome. Some approaches have been p...

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Autores principales: Chiocchia, Virginia, Furukawa, Toshi A., Schneider-Thoma, Johannes, Siafis, Spyridon, Cipriani, Andrea, Leucht, Stefan, Salanti, Georgia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638812/
https://www.ncbi.nlm.nih.gov/pubmed/37951949
http://dx.doi.org/10.1186/s13643-023-02376-1
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author Chiocchia, Virginia
Furukawa, Toshi A.
Schneider-Thoma, Johannes
Siafis, Spyridon
Cipriani, Andrea
Leucht, Stefan
Salanti, Georgia
author_facet Chiocchia, Virginia
Furukawa, Toshi A.
Schneider-Thoma, Johannes
Siafis, Spyridon
Cipriani, Andrea
Leucht, Stefan
Salanti, Georgia
author_sort Chiocchia, Virginia
collection PubMed
description BACKGROUND: The relative treatment effects estimated from network meta-analysis can be employed to rank treatments from the most preferable to the least preferable option. These treatment hierarchies are typically based on ranking metrics calculated from a single outcome. Some approaches have been proposed in the literature to account for multiple outcomes and individual preferences, such as the coverage area inside a spie chart, that, however, does not account for a trade-off between efficacy and safety outcomes. We present the net-benefit standardised area within a spie chart, [Formula: see text] to explore the changes in treatment performance with different trade-offs between benefits and harms, according to a particular set of preferences. METHODS: We combine the standardised areas within spie charts for efficacy and safety/acceptability outcomes with a value λ specifying the trade-off between benefits and harms. We derive absolute probabilities and convert outcomes on a scale between 0 and 1 for inclusion in the spie chart. RESULTS: We illustrate how the treatments in three published network meta-analyses perform as the trade-off λ varies. The decrease of the [Formula: see text] quantity appears more pronounced for some drugs, e.g. haloperidol. Changes in treatment performance seem more frequent when SUCRA is employed as outcome measures in the spie charts. CONCLUSIONS: [Formula: see text] should not be interpreted as a ranking metric but it is a simple approach that could help identify which treatment is preferable when multiple outcomes are of interest and trading-off between benefits and harms is important. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-023-02376-1.
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spelling pubmed-106388122023-11-11 Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis Chiocchia, Virginia Furukawa, Toshi A. Schneider-Thoma, Johannes Siafis, Spyridon Cipriani, Andrea Leucht, Stefan Salanti, Georgia Syst Rev Methodology BACKGROUND: The relative treatment effects estimated from network meta-analysis can be employed to rank treatments from the most preferable to the least preferable option. These treatment hierarchies are typically based on ranking metrics calculated from a single outcome. Some approaches have been proposed in the literature to account for multiple outcomes and individual preferences, such as the coverage area inside a spie chart, that, however, does not account for a trade-off between efficacy and safety outcomes. We present the net-benefit standardised area within a spie chart, [Formula: see text] to explore the changes in treatment performance with different trade-offs between benefits and harms, according to a particular set of preferences. METHODS: We combine the standardised areas within spie charts for efficacy and safety/acceptability outcomes with a value λ specifying the trade-off between benefits and harms. We derive absolute probabilities and convert outcomes on a scale between 0 and 1 for inclusion in the spie chart. RESULTS: We illustrate how the treatments in three published network meta-analyses perform as the trade-off λ varies. The decrease of the [Formula: see text] quantity appears more pronounced for some drugs, e.g. haloperidol. Changes in treatment performance seem more frequent when SUCRA is employed as outcome measures in the spie charts. CONCLUSIONS: [Formula: see text] should not be interpreted as a ranking metric but it is a simple approach that could help identify which treatment is preferable when multiple outcomes are of interest and trading-off between benefits and harms is important. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-023-02376-1. BioMed Central 2023-11-11 /pmc/articles/PMC10638812/ /pubmed/37951949 http://dx.doi.org/10.1186/s13643-023-02376-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology
Chiocchia, Virginia
Furukawa, Toshi A.
Schneider-Thoma, Johannes
Siafis, Spyridon
Cipriani, Andrea
Leucht, Stefan
Salanti, Georgia
Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis
title Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis
title_full Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis
title_fullStr Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis
title_full_unstemmed Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis
title_short Estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis
title_sort estimating and visualising the trade-off between benefits and harms on multiple clinical outcomes in network meta-analysis
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638812/
https://www.ncbi.nlm.nih.gov/pubmed/37951949
http://dx.doi.org/10.1186/s13643-023-02376-1
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