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

Authors
 San Lee  ;  Keum Hwa Lee  ;  Kyung Mee Park  ;  Sung Jong Park  ;  Won Jae Kim  ;  Jinhee Lee  ;  Andreas Kronbichler  ;  Lee Smith  ;  Marco Solmi  ;  Brendon Stubbs  ;  Ai Koyanagi  ;  Louis Jacob  ;  Andrew Stickley  ;  Trevor Thompson  ;  Elena Dragioti  ;  Hans Oh  ;  Andre R Brunoni  ;  Andre F Carvalho  ;  Joaquim Radua  ;  Suk Kyoon An  ;  Kee Namkoong  ;  Eun Lee  ;  Jae Il Shin  ;  Paolo Fusar-Poli 
Citation
 PSYCHOLOGICAL MEDICINE, : epub., 2021-11 
Journal Title
PSYCHOLOGICAL MEDICINE
ISSN
 0033-2917 
Issue Date
2021-11
Keywords
Data extraction error ; depression ; inflammatory biomarker ; meta-analysis ; umbrella review
Abstract
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-α (TNF-α), interleukin 1-β (IL-1β), 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- α, IL-6, CRP, but not IL-1β, 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.
Full Text
https://www.cambridge.org/core/journals/psychological-medicine/article/impact-of-data-extraction-errors-in-metaanalyses-on-the-association-between-depression-and-peripheral-inflammatory-biomarkers-an-umbrella-review/A1CC860BA1ABCBBCFEC75A0491A720DE
DOI
10.1017/S0033291721003767
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Pediatrics (소아과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Psychiatry (정신과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Won Jae(김원재) ORCID logo https://orcid.org/0000-0003-3472-5432
Namkoong, Kee(남궁기) ORCID logo https://orcid.org/0000-0003-1400-8057
Shin, Jae Il(신재일) ORCID logo https://orcid.org/0000-0003-2326-1820
An, Suk Kyoon(안석균) ORCID logo https://orcid.org/0000-0003-4576-6184
Lee, Keum Hwa(이금화) ORCID logo https://orcid.org/0000-0002-1511-9587
Lee, San(이산) ORCID logo https://orcid.org/0000-0003-4834-8463
Lee, Eun(이은) ORCID logo https://orcid.org/0000-0002-7462-0144
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/187214
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