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From living systematic reviews to meta-analytical research domains
Because of the rapidly increasing number of randomised controlled trials (RCTs) and meta-analyses in many fields, there is an urgent need to step up from meta-analyses to higher levels of aggregation of outcomes of RCTs. Network meta-analyses and umbrella reviews allow higher levels of aggregation o...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9685685/ https://www.ncbi.nlm.nih.gov/pubmed/35853730 http://dx.doi.org/10.1136/ebmental-2022-300509 |
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author | Cuijpers, Pim Miguel, Clara Papola, Davide Harrer, Mathias Karyotaki, Eirini |
author_facet | Cuijpers, Pim Miguel, Clara Papola, Davide Harrer, Mathias Karyotaki, Eirini |
author_sort | Cuijpers, Pim |
collection | PubMed |
description | Because of the rapidly increasing number of randomised controlled trials (RCTs) and meta-analyses in many fields, there is an urgent need to step up from meta-analyses to higher levels of aggregation of outcomes of RCTs. Network meta-analyses and umbrella reviews allow higher levels of aggregation of RCT outcomes, but cannot adequately cover the evidence for a whole field. The ‘Meta-Analytic Research Domain’ (MARD) may be a new methodology to aggregate RCT data of a whole field. A MARD is a living systematic review of a research domain that cannot be covered by one PICO. For example, a MARD of psychotherapy for depression covers all RCTs comparing the effects of all types of psychotherapy to control conditions, to each other, to pharmacotherapy and combined treatment. It also covers all RCTs comparing treatment formats, the effects in different target groups, subtypes of depression and secondary outcomes. Although the time and resources needed to build a MARD are considerable, they offer many advantages, including a comprehensive and consistent overview of a research field and important meta-analytic studies that cannot be conducted with conventional methods. MARDs are a promising method to step up the aggregation of RCTs to a next level and it is highly relevant to work out the methods of this approach in a more detailed way. |
format | Online Article Text |
id | pubmed-9685685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-96856852022-11-25 From living systematic reviews to meta-analytical research domains Cuijpers, Pim Miguel, Clara Papola, Davide Harrer, Mathias Karyotaki, Eirini Evid Based Ment Health Perspective Because of the rapidly increasing number of randomised controlled trials (RCTs) and meta-analyses in many fields, there is an urgent need to step up from meta-analyses to higher levels of aggregation of outcomes of RCTs. Network meta-analyses and umbrella reviews allow higher levels of aggregation of RCT outcomes, but cannot adequately cover the evidence for a whole field. The ‘Meta-Analytic Research Domain’ (MARD) may be a new methodology to aggregate RCT data of a whole field. A MARD is a living systematic review of a research domain that cannot be covered by one PICO. For example, a MARD of psychotherapy for depression covers all RCTs comparing the effects of all types of psychotherapy to control conditions, to each other, to pharmacotherapy and combined treatment. It also covers all RCTs comparing treatment formats, the effects in different target groups, subtypes of depression and secondary outcomes. Although the time and resources needed to build a MARD are considerable, they offer many advantages, including a comprehensive and consistent overview of a research field and important meta-analytic studies that cannot be conducted with conventional methods. MARDs are a promising method to step up the aggregation of RCTs to a next level and it is highly relevant to work out the methods of this approach in a more detailed way. BMJ Publishing Group 2022-11 2022-07-19 /pmc/articles/PMC9685685/ /pubmed/35853730 http://dx.doi.org/10.1136/ebmental-2022-300509 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Perspective Cuijpers, Pim Miguel, Clara Papola, Davide Harrer, Mathias Karyotaki, Eirini From living systematic reviews to meta-analytical research domains |
title | From living systematic reviews to meta-analytical research domains |
title_full | From living systematic reviews to meta-analytical research domains |
title_fullStr | From living systematic reviews to meta-analytical research domains |
title_full_unstemmed | From living systematic reviews to meta-analytical research domains |
title_short | From living systematic reviews to meta-analytical research domains |
title_sort | from living systematic reviews to meta-analytical research domains |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9685685/ https://www.ncbi.nlm.nih.gov/pubmed/35853730 http://dx.doi.org/10.1136/ebmental-2022-300509 |
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