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Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies

In recent years, the number of mathematical modelling studies has increased steeply. Many of the questions addressed in these studies are relevant to the development of World Health Organization (WHO) guidelines, but modelling studies are rarely formally included as part of the body of evidence. An...

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Autores principales: Egger, Matthias, Johnson, Leigh, Althaus, Christian, Schöni, Anna, Salanti, Georgia, Low, Nicola, Norris, Susan L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829466/
https://www.ncbi.nlm.nih.gov/pubmed/29552335
http://dx.doi.org/10.12688/f1000research.12367.2
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author Egger, Matthias
Johnson, Leigh
Althaus, Christian
Schöni, Anna
Salanti, Georgia
Low, Nicola
Norris, Susan L.
author_facet Egger, Matthias
Johnson, Leigh
Althaus, Christian
Schöni, Anna
Salanti, Georgia
Low, Nicola
Norris, Susan L.
author_sort Egger, Matthias
collection PubMed
description In recent years, the number of mathematical modelling studies has increased steeply. Many of the questions addressed in these studies are relevant to the development of World Health Organization (WHO) guidelines, but modelling studies are rarely formally included as part of the body of evidence. An expert consultation hosted by WHO, a survey of modellers and users of modelling studies, and literature reviews informed the development of recommendations on when and how to incorporate the results of modelling studies into WHO guidelines. In this article, we argue that modelling studies should routinely be considered in the process of developing WHO guidelines, but particularly in the evaluation of public health programmes, long-term effectiveness or comparative effectiveness.  There should be a systematic and transparent approach to identifying relevant published models, and to commissioning new models.  We believe that the inclusion of evidence from modelling studies into the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process is possible and desirable, with relatively few adaptations.  No single “one-size-fits-all” approach is appropriate to assess the quality of modelling studies. The concept of the ‘credibility’ of the model, which takes the conceptualization of the problem, model structure, input data, different dimensions of uncertainty, as well as transparency and validation into account, is more appropriate than ‘risk of bias’.
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spelling pubmed-58294662018-03-16 Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies Egger, Matthias Johnson, Leigh Althaus, Christian Schöni, Anna Salanti, Georgia Low, Nicola Norris, Susan L. F1000Res Opinion Article In recent years, the number of mathematical modelling studies has increased steeply. Many of the questions addressed in these studies are relevant to the development of World Health Organization (WHO) guidelines, but modelling studies are rarely formally included as part of the body of evidence. An expert consultation hosted by WHO, a survey of modellers and users of modelling studies, and literature reviews informed the development of recommendations on when and how to incorporate the results of modelling studies into WHO guidelines. In this article, we argue that modelling studies should routinely be considered in the process of developing WHO guidelines, but particularly in the evaluation of public health programmes, long-term effectiveness or comparative effectiveness.  There should be a systematic and transparent approach to identifying relevant published models, and to commissioning new models.  We believe that the inclusion of evidence from modelling studies into the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process is possible and desirable, with relatively few adaptations.  No single “one-size-fits-all” approach is appropriate to assess the quality of modelling studies. The concept of the ‘credibility’ of the model, which takes the conceptualization of the problem, model structure, input data, different dimensions of uncertainty, as well as transparency and validation into account, is more appropriate than ‘risk of bias’. F1000 Research Limited 2018-02-26 /pmc/articles/PMC5829466/ /pubmed/29552335 http://dx.doi.org/10.12688/f1000research.12367.2 Text en Copyright: © 2018 Egger M et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Opinion Article
Egger, Matthias
Johnson, Leigh
Althaus, Christian
Schöni, Anna
Salanti, Georgia
Low, Nicola
Norris, Susan L.
Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies
title Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies
title_full Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies
title_fullStr Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies
title_full_unstemmed Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies
title_short Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies
title_sort developing who guidelines: time to formally include evidence from mathematical modelling studies
topic Opinion Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829466/
https://www.ncbi.nlm.nih.gov/pubmed/29552335
http://dx.doi.org/10.12688/f1000research.12367.2
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