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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2018
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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’. |
format | Online Article Text |
id | pubmed-5829466 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
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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