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Mapping Strategies to Assess and Increase the Validity of Published Disproportionality Signals: A Meta-Research Study

BACKGROUND AND AIM: Disproportionality analysis is traditionally used in spontaneous reporting systems to generate working hypotheses about potential adverse drug reactions: the so-called disproportionality signals. We aim to map the methods used by researchers to assess and increase the validity of...

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Autores principales: Fusaroli, Michele, Salvo, Francesco, Bernardeau, Claire, Idris, Maryam, Dolladille, Charles, Pariente, Antoine, Poluzzi, Elisabetta, Raschi, Emanuel, Khouri, Charles
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442263/
https://www.ncbi.nlm.nih.gov/pubmed/37421568
http://dx.doi.org/10.1007/s40264-023-01329-w
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author Fusaroli, Michele
Salvo, Francesco
Bernardeau, Claire
Idris, Maryam
Dolladille, Charles
Pariente, Antoine
Poluzzi, Elisabetta
Raschi, Emanuel
Khouri, Charles
author_facet Fusaroli, Michele
Salvo, Francesco
Bernardeau, Claire
Idris, Maryam
Dolladille, Charles
Pariente, Antoine
Poluzzi, Elisabetta
Raschi, Emanuel
Khouri, Charles
author_sort Fusaroli, Michele
collection PubMed
description BACKGROUND AND AIM: Disproportionality analysis is traditionally used in spontaneous reporting systems to generate working hypotheses about potential adverse drug reactions: the so-called disproportionality signals. We aim to map the methods used by researchers to assess and increase the validity of their published disproportionality signals. METHODS: From a systematic literature search of published disproportionality analyses up until 1 January 2020, we randomly selected and analyzed 100 studies. We considered five domains: (1) rationale for the study, (2) design of disproportionality analyses, (3) case-by-case assessment, (4) use of complementary data sources, and (5) contextualization of the results within existing evidence. RESULTS: Among the articles, multiple strategies were adopted to assess and enhance the results validity. The rationale, in 95 articles, was explicitly referred to the accrued evidence, mostly observational data (n = 46) and regulatory documents (n = 45). A statistical adjustment was performed in 34 studies, and specific strategies to correct for biases were implemented in 33 studies. A case-by-case assessment was complementarily performed in 35 studies, most often by investigating temporal plausibility (n = 26). Complementary data sources were used in 25 articles. In 78 articles, results were contextualized using accrued evidence from the literature and regulatory documents, the most important sources being observational (n = 45), other disproportionalities (n = 37), and case reports (n = 36). CONCLUSIONS: This meta-research study highlighted the heterogeneity in methods and strategies used by researchers to assess the validity of disproportionality signals. Mapping these strategies is a first step towards testing their utility in different scenarios and developing guidelines for designing future disproportionality analysis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40264-023-01329-w.
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spelling pubmed-104422632023-08-23 Mapping Strategies to Assess and Increase the Validity of Published Disproportionality Signals: A Meta-Research Study Fusaroli, Michele Salvo, Francesco Bernardeau, Claire Idris, Maryam Dolladille, Charles Pariente, Antoine Poluzzi, Elisabetta Raschi, Emanuel Khouri, Charles Drug Saf Original Research Article BACKGROUND AND AIM: Disproportionality analysis is traditionally used in spontaneous reporting systems to generate working hypotheses about potential adverse drug reactions: the so-called disproportionality signals. We aim to map the methods used by researchers to assess and increase the validity of their published disproportionality signals. METHODS: From a systematic literature search of published disproportionality analyses up until 1 January 2020, we randomly selected and analyzed 100 studies. We considered five domains: (1) rationale for the study, (2) design of disproportionality analyses, (3) case-by-case assessment, (4) use of complementary data sources, and (5) contextualization of the results within existing evidence. RESULTS: Among the articles, multiple strategies were adopted to assess and enhance the results validity. The rationale, in 95 articles, was explicitly referred to the accrued evidence, mostly observational data (n = 46) and regulatory documents (n = 45). A statistical adjustment was performed in 34 studies, and specific strategies to correct for biases were implemented in 33 studies. A case-by-case assessment was complementarily performed in 35 studies, most often by investigating temporal plausibility (n = 26). Complementary data sources were used in 25 articles. In 78 articles, results were contextualized using accrued evidence from the literature and regulatory documents, the most important sources being observational (n = 45), other disproportionalities (n = 37), and case reports (n = 36). CONCLUSIONS: This meta-research study highlighted the heterogeneity in methods and strategies used by researchers to assess the validity of disproportionality signals. Mapping these strategies is a first step towards testing their utility in different scenarios and developing guidelines for designing future disproportionality analysis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40264-023-01329-w. Springer International Publishing 2023-07-08 2023 /pmc/articles/PMC10442263/ /pubmed/37421568 http://dx.doi.org/10.1007/s40264-023-01329-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial 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-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research Article
Fusaroli, Michele
Salvo, Francesco
Bernardeau, Claire
Idris, Maryam
Dolladille, Charles
Pariente, Antoine
Poluzzi, Elisabetta
Raschi, Emanuel
Khouri, Charles
Mapping Strategies to Assess and Increase the Validity of Published Disproportionality Signals: A Meta-Research Study
title Mapping Strategies to Assess and Increase the Validity of Published Disproportionality Signals: A Meta-Research Study
title_full Mapping Strategies to Assess and Increase the Validity of Published Disproportionality Signals: A Meta-Research Study
title_fullStr Mapping Strategies to Assess and Increase the Validity of Published Disproportionality Signals: A Meta-Research Study
title_full_unstemmed Mapping Strategies to Assess and Increase the Validity of Published Disproportionality Signals: A Meta-Research Study
title_short Mapping Strategies to Assess and Increase the Validity of Published Disproportionality Signals: A Meta-Research Study
title_sort mapping strategies to assess and increase the validity of published disproportionality signals: a meta-research study
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442263/
https://www.ncbi.nlm.nih.gov/pubmed/37421568
http://dx.doi.org/10.1007/s40264-023-01329-w
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