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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2021
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| _version_ | 1864513559591911424 |
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| 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 |