Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses
Abstract Background Individual participant data meta-analyses (IPD-MAs), which involve harmonising and analysing participant-level data from related studies, provide several advantages over aggregate data meta-analyses, which pool study-level findings. IPD-MAs are especially important for building a...
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Format: | Article |
Language: | English |
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BMC
2023-07-01
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Series: | BMC Health Services Research |
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Online Access: | https://doi.org/10.1186/s12913-023-09726-8 |
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author | Lauren Maxwell Priya Shreedhar Brooke Levis Sayali Arvind Chavan Shaila Akter Mabel Carabali |
author_facet | Lauren Maxwell Priya Shreedhar Brooke Levis Sayali Arvind Chavan Shaila Akter Mabel Carabali |
author_sort | Lauren Maxwell |
collection | DOAJ |
description | Abstract Background Individual participant data meta-analyses (IPD-MAs), which involve harmonising and analysing participant-level data from related studies, provide several advantages over aggregate data meta-analyses, which pool study-level findings. IPD-MAs are especially important for building and evaluating diagnostic and prognostic models, making them an important tool for informing the research and public health responses to COVID-19. Methods We conducted a rapid systematic review of protocols and publications from planned, ongoing, or completed COVID-19-related IPD-MAs to identify areas of overlap and maximise data request and harmonisation efforts. We searched four databases using a combination of text and MeSH terms. Two independent reviewers determined eligibility at the title-abstract and full-text stages. Data were extracted by one reviewer into a pretested data extraction form and subsequently reviewed by a second reviewer. Data were analysed using a narrative synthesis approach. A formal risk of bias assessment was not conducted. Results We identified 31 COVID-19-related IPD-MAs, including five living IPD-MAs and ten IPD-MAs that limited their inference to published data (e.g., case reports). We found overlap in study designs, populations, exposures, and outcomes of interest. For example, 26 IPD-MAs included RCTs; 17 IPD-MAs were limited to hospitalised patients. Sixteen IPD-MAs focused on evaluating medical treatments, including six IPD-MAs for antivirals, four on antibodies, and two that evaluated convalescent plasma. Conclusions Collaboration across related IPD-MAs can leverage limited resources and expertise by expediting the creation of cross-study participant-level data datasets, which can, in turn, fast-track evidence synthesis for the improved diagnosis and treatment of COVID-19. Trial registration 10.17605/OSF.IO/93GF2. |
first_indexed | 2024-03-09T15:22:48Z |
format | Article |
id | doaj.art-ced149e0c9d34926b939f732976600fa |
institution | Directory Open Access Journal |
issn | 1472-6963 |
language | English |
last_indexed | 2024-03-09T15:22:48Z |
publishDate | 2023-07-01 |
publisher | BMC |
record_format | Article |
series | BMC Health Services Research |
spelling | doaj.art-ced149e0c9d34926b939f732976600fa2023-11-26T12:43:23ZengBMCBMC Health Services Research1472-69632023-07-0123111310.1186/s12913-023-09726-8Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analysesLauren Maxwell0Priya Shreedhar1Brooke Levis2Sayali Arvind Chavan3Shaila Akter4Mabel Carabali5Heidelberger Institut Für Global Health, Universitätsklinikum HeidelbergHeidelberger Institut Für Global Health, Universitätsklinikum HeidelbergCentre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General HospitalInstitute of Tropical Medicine and Public Health, Charité – Universitätsmedizin BerlinHeidelberger Institut Für Global Health, Universitätsklinikum HeidelbergDepartment of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill UniversityAbstract Background Individual participant data meta-analyses (IPD-MAs), which involve harmonising and analysing participant-level data from related studies, provide several advantages over aggregate data meta-analyses, which pool study-level findings. IPD-MAs are especially important for building and evaluating diagnostic and prognostic models, making them an important tool for informing the research and public health responses to COVID-19. Methods We conducted a rapid systematic review of protocols and publications from planned, ongoing, or completed COVID-19-related IPD-MAs to identify areas of overlap and maximise data request and harmonisation efforts. We searched four databases using a combination of text and MeSH terms. Two independent reviewers determined eligibility at the title-abstract and full-text stages. Data were extracted by one reviewer into a pretested data extraction form and subsequently reviewed by a second reviewer. Data were analysed using a narrative synthesis approach. A formal risk of bias assessment was not conducted. Results We identified 31 COVID-19-related IPD-MAs, including five living IPD-MAs and ten IPD-MAs that limited their inference to published data (e.g., case reports). We found overlap in study designs, populations, exposures, and outcomes of interest. For example, 26 IPD-MAs included RCTs; 17 IPD-MAs were limited to hospitalised patients. Sixteen IPD-MAs focused on evaluating medical treatments, including six IPD-MAs for antivirals, four on antibodies, and two that evaluated convalescent plasma. Conclusions Collaboration across related IPD-MAs can leverage limited resources and expertise by expediting the creation of cross-study participant-level data datasets, which can, in turn, fast-track evidence synthesis for the improved diagnosis and treatment of COVID-19. Trial registration 10.17605/OSF.IO/93GF2.https://doi.org/10.1186/s12913-023-09726-8COVID-19Individual participant data meta-analysisMeta-analysisData sharing |
spellingShingle | Lauren Maxwell Priya Shreedhar Brooke Levis Sayali Arvind Chavan Shaila Akter Mabel Carabali Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses BMC Health Services Research COVID-19 Individual participant data meta-analysis Meta-analysis Data sharing |
title | Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses |
title_full | Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses |
title_fullStr | Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses |
title_full_unstemmed | Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses |
title_short | Overlapping research efforts in a global pandemic: a rapid systematic review of COVID-19-related individual participant data meta-analyses |
title_sort | overlapping research efforts in a global pandemic a rapid systematic review of covid 19 related individual participant data meta analyses |
topic | COVID-19 Individual participant data meta-analysis Meta-analysis Data sharing |
url | https://doi.org/10.1186/s12913-023-09726-8 |
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