Impact of data extraction errors in meta-analyses on the association between depression and peripheral inflammatory biomarkers: an umbrella review.

BACKGROUND: Accumulating evidence suggests that alterations in inflammatory biomarkers are important in depression. However, previous meta-analyses disagree on these associations, and errors in data extraction may account for these discrepancies. METHODS: PubMed/MEDLINE, Embase, PsycINFO, and the Co...

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Detalhes bibliográficos
Autores: Lee S, Lee KH, Park KM, Park SJ, Kim WJ, Lee J, Kronbichler A, Smith L, Solmi M, Stubbs B, Koyanagi A, Jacob L, Stickley A, Thompson T, Dragioti E, Oh H, Brunoni AR, Carvalho AF, Radua J, An SK, Namkoong K, Lee E, Shin JI, Fusar-Poli P
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2023
País:España
Recursos:Fundació Sant Joan de Déu
Repositório:r-FSJD. Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu
OAI Identifier:oai:fsjd.fundanetsuite.com:p20308
Acesso em linha:https://fsjd.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=20308
Access Level:Acceso aberto
Palavra-chave:Data extraction error
depression
inflammatory biomarker
meta-analysis
umbrella review
Descrição
Resumo:BACKGROUND: Accumulating evidence suggests that alterations in inflammatory biomarkers are important in depression. However, previous meta-analyses disagree on these associations, and errors in data extraction may account for these discrepancies. METHODS: PubMed/MEDLINE, Embase, PsycINFO, and the Cochrane Library were searched from database inception to 14 January 2020. Meta-analyses of observational studies examining the association between depression and levels of tumor necrosis factor-a (TNF-a), interleukin 1-ß (IL-1ß), interleukin-6 (IL-6), and C-reactive protein (CRP) were eligible. Errors were classified as follows: incorrect sample sizes, incorrectly used standard deviation, incorrect participant inclusion, calculation error, or analysis with insufficient data. We determined their impact on the results after correction thereof. RESULTS: Errors were noted in 14 of the 15 meta-analyses included. Across 521 primary studies, 118 (22.6%) showed the following errors: incorrect sample sizes (20 studies, 16.9%), incorrect use of standard deviation (35 studies, 29.7%), incorrect participant inclusion (7 studies, 5.9%), calculation errors (33 studies, 28.0%), and analysis with insufficient data (23 studies, 19.5%). After correcting these errors, 11 (29.7%) out of 37 pooled effect sizes changed by a magnitude of more than 0.1, ranging from 0.11 to 1.15. The updated meta-analyses showed that elevated levels of TNF- a, IL-6, CRP, but not IL-1ß, are associated with depression. CONCLUSIONS: These findings show that data extraction errors in meta-analyses can impact findings. Efforts to reduce such errors are important in studies of the association between depression and peripheral inflammatory biomarkers, for which high heterogeneity and conflicting results have been continuously reported.