A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies

<h3>Objective</h3><p dir="ltr">In evidence synthesis practice, researchers often face the problem of how to deal with zero-events. Inappropriately dealing with zero-events studies may lead to research waste and mislead healthcare practice. We propose a framework to guide...

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Main Author: Chang Xu (102022) (author)
Other Authors: Luis Furuya-Kanamori (477124) (author), Liliane Zorzela (10970928) (author), Lifeng Lin (2034385) (author), Sunita Vohra (130014) (author)
Published: 2021
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_version_ 1864513559591911424
author Chang Xu (102022)
author2 Luis Furuya-Kanamori (477124)
Liliane Zorzela (10970928)
Lifeng Lin (2034385)
Sunita Vohra (130014)
author2_role author
author
author
author
author_facet Chang Xu (102022)
Luis Furuya-Kanamori (477124)
Liliane Zorzela (10970928)
Lifeng Lin (2034385)
Sunita Vohra (130014)
author_role author
dc.creator.none.fl_str_mv Chang Xu (102022)
Luis Furuya-Kanamori (477124)
Liliane Zorzela (10970928)
Lifeng Lin (2034385)
Sunita Vohra (130014)
dc.date.none.fl_str_mv 2021-02-12T00:00:00Z
dc.identifier.none.fl_str_mv 10.1016/j.jclinepi.2021.02.012
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/A_proposed_framework_to_guide_evidence_synthesis_practice_for_meta-analysis_with_zero-events_studies/24083097
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Health sciences
Epidemiology
Mathematical sciences
Statistics
Meta-analysis
Zero-events studies
Classification framework
Guideline
Evidence synthesis practice
Decision-making
dc.title.none.fl_str_mv A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <h3>Objective</h3><p dir="ltr">In evidence synthesis practice, researchers often face the problem of how to deal with zero-events. Inappropriately dealing with zero-events studies may lead to research waste and mislead healthcare practice. We propose a framework to guide researchers to better deal with zero-events in meta-analysis.</p><h3>Study design and setting</h3><p dir="ltr">We used two dimensions, one with respect to the total events count across all studies in the comparative arms in a meta-analysis, and a second with respect to whether included studies have single or both arms with zero-events, to establish the framework for the classification of meta-analysis with zero-events studies. A dataset from Cochrane systematic reviews was used to evaluate the classification.</p><h3>Results</h3><p dir="ltr">The proposed framework classifies meta-analysis with zero-events studies into six subtypes. The classification matched well to the large real-world dataset. The applicability of existing methods for zero-events were then presented under each meta-analysis subtype based on this framework, with a 5-step principle to help researchers in evidence synthesis practice.</p><h3>Conclusions</h3><p dir="ltr">The proposed framework should be considered by researchers when making decisions on the selection of the synthesis methods in a meta-analysis. It also provides a reasonable basis for the development of methodological guidelines to deal with zero-events in meta-analysis.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Clinical Epidemiology<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.jclinepi.2021.02.012" target="_blank">https://dx.doi.org/10.1016/j.jclinepi.2021.02.012</a></p>
eu_rights_str_mv openAccess
id Manara2_c1d4b1addbe9e484ee59bcdb42df4fe0
identifier_str_mv 10.1016/j.jclinepi.2021.02.012
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/24083097
publishDate 2021
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studiesChang Xu (102022)Luis Furuya-Kanamori (477124)Liliane Zorzela (10970928)Lifeng Lin (2034385)Sunita Vohra (130014)Health sciencesEpidemiologyMathematical sciencesStatisticsMeta-analysisZero-events studiesClassification frameworkGuidelineEvidence synthesis practiceDecision-making<h3>Objective</h3><p dir="ltr">In evidence synthesis practice, researchers often face the problem of how to deal with zero-events. Inappropriately dealing with zero-events studies may lead to research waste and mislead healthcare practice. We propose a framework to guide researchers to better deal with zero-events in meta-analysis.</p><h3>Study design and setting</h3><p dir="ltr">We used two dimensions, one with respect to the total events count across all studies in the comparative arms in a meta-analysis, and a second with respect to whether included studies have single or both arms with zero-events, to establish the framework for the classification of meta-analysis with zero-events studies. A dataset from Cochrane systematic reviews was used to evaluate the classification.</p><h3>Results</h3><p dir="ltr">The proposed framework classifies meta-analysis with zero-events studies into six subtypes. The classification matched well to the large real-world dataset. The applicability of existing methods for zero-events were then presented under each meta-analysis subtype based on this framework, with a 5-step principle to help researchers in evidence synthesis practice.</p><h3>Conclusions</h3><p dir="ltr">The proposed framework should be considered by researchers when making decisions on the selection of the synthesis methods in a meta-analysis. It also provides a reasonable basis for the development of methodological guidelines to deal with zero-events in meta-analysis.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Clinical Epidemiology<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.jclinepi.2021.02.012" target="_blank">https://dx.doi.org/10.1016/j.jclinepi.2021.02.012</a></p>2021-02-12T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.jclinepi.2021.02.012https://figshare.com/articles/journal_contribution/A_proposed_framework_to_guide_evidence_synthesis_practice_for_meta-analysis_with_zero-events_studies/24083097CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/240830972021-02-12T00:00:00Z
spellingShingle A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies
Chang Xu (102022)
Health sciences
Epidemiology
Mathematical sciences
Statistics
Meta-analysis
Zero-events studies
Classification framework
Guideline
Evidence synthesis practice
Decision-making
status_str publishedVersion
title A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies
title_full A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies
title_fullStr A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies
title_full_unstemmed A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies
title_short A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies
title_sort A proposed framework to guide evidence synthesis practice for meta-analysis with zero-events studies
topic Health sciences
Epidemiology
Mathematical sciences
Statistics
Meta-analysis
Zero-events studies
Classification framework
Guideline
Evidence synthesis practice
Decision-making