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Recommendations for the use of propensity score methods in multiple sclerosis research

BACKGROUND: With many disease-modifying therapies currently approved for the management of multiple sclerosis, there is a growing need to evaluate the comparative effectiveness and safety of those therapies from real-world data sources. Propensity score methods have recently gained popularity in mul...

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Autores principales: Simoneau, Gabrielle, Pellegrini, Fabio, Debray, Thomas PA, Rouette, Julie, Muñoz, Johanna, Platt, Robert W., Petkau, John, Bohn, Justin, Shen, Changyu, de Moor, Carl, Karim, Mohammad Ehsanul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260471/
https://www.ncbi.nlm.nih.gov/pubmed/35387508
http://dx.doi.org/10.1177/13524585221085733
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author Simoneau, Gabrielle
Pellegrini, Fabio
Debray, Thomas PA
Rouette, Julie
Muñoz, Johanna
Platt, Robert W.
Petkau, John
Bohn, Justin
Shen, Changyu
de Moor, Carl
Karim, Mohammad Ehsanul
author_facet Simoneau, Gabrielle
Pellegrini, Fabio
Debray, Thomas PA
Rouette, Julie
Muñoz, Johanna
Platt, Robert W.
Petkau, John
Bohn, Justin
Shen, Changyu
de Moor, Carl
Karim, Mohammad Ehsanul
author_sort Simoneau, Gabrielle
collection PubMed
description BACKGROUND: With many disease-modifying therapies currently approved for the management of multiple sclerosis, there is a growing need to evaluate the comparative effectiveness and safety of those therapies from real-world data sources. Propensity score methods have recently gained popularity in multiple sclerosis research to generate real-world evidence. Recent evidence suggests, however, that the conduct and reporting of propensity score analyses are often suboptimal in multiple sclerosis studies. OBJECTIVES: To provide practical guidance to clinicians and researchers on the use of propensity score methods within the context of multiple sclerosis research. METHODS: We summarize recommendations on the use of propensity score matching and weighting based on the current methodological literature, and provide examples of good practice. RESULTS: Step-by-step recommendations are presented, starting with covariate selection and propensity score estimation, followed by guidance on the assessment of covariate balance and implementation of propensity score matching and weighting. Finally, we focus on treatment effect estimation and sensitivity analyses. CONCLUSION: This comprehensive set of recommendations highlights key elements that require careful attention when using propensity score methods.
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spelling pubmed-92604712022-07-08 Recommendations for the use of propensity score methods in multiple sclerosis research Simoneau, Gabrielle Pellegrini, Fabio Debray, Thomas PA Rouette, Julie Muñoz, Johanna Platt, Robert W. Petkau, John Bohn, Justin Shen, Changyu de Moor, Carl Karim, Mohammad Ehsanul Mult Scler Future Perspectives BACKGROUND: With many disease-modifying therapies currently approved for the management of multiple sclerosis, there is a growing need to evaluate the comparative effectiveness and safety of those therapies from real-world data sources. Propensity score methods have recently gained popularity in multiple sclerosis research to generate real-world evidence. Recent evidence suggests, however, that the conduct and reporting of propensity score analyses are often suboptimal in multiple sclerosis studies. OBJECTIVES: To provide practical guidance to clinicians and researchers on the use of propensity score methods within the context of multiple sclerosis research. METHODS: We summarize recommendations on the use of propensity score matching and weighting based on the current methodological literature, and provide examples of good practice. RESULTS: Step-by-step recommendations are presented, starting with covariate selection and propensity score estimation, followed by guidance on the assessment of covariate balance and implementation of propensity score matching and weighting. Finally, we focus on treatment effect estimation and sensitivity analyses. CONCLUSION: This comprehensive set of recommendations highlights key elements that require careful attention when using propensity score methods. SAGE Publications 2022-04-06 2022-08 /pmc/articles/PMC9260471/ /pubmed/35387508 http://dx.doi.org/10.1177/13524585221085733 Text en © The Author(s), 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Future Perspectives
Simoneau, Gabrielle
Pellegrini, Fabio
Debray, Thomas PA
Rouette, Julie
Muñoz, Johanna
Platt, Robert W.
Petkau, John
Bohn, Justin
Shen, Changyu
de Moor, Carl
Karim, Mohammad Ehsanul
Recommendations for the use of propensity score methods in multiple sclerosis research
title Recommendations for the use of propensity score methods in multiple sclerosis research
title_full Recommendations for the use of propensity score methods in multiple sclerosis research
title_fullStr Recommendations for the use of propensity score methods in multiple sclerosis research
title_full_unstemmed Recommendations for the use of propensity score methods in multiple sclerosis research
title_short Recommendations for the use of propensity score methods in multiple sclerosis research
title_sort recommendations for the use of propensity score methods in multiple sclerosis research
topic Future Perspectives
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260471/
https://www.ncbi.nlm.nih.gov/pubmed/35387508
http://dx.doi.org/10.1177/13524585221085733
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