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

Lee, San and Lee, Keum Hwa and Park, Kyung Mee and Park, Sung Jong and Kim, Won Jae and Lee, Jinhee and Kronbichler, Andreas and Smith, Lee and Solmi, Marco and Stubbs, Brendon and Koyanagi, Ai and Jacob, Louis and Stickley, Andrew and Thompson, Trevor and Dragioti, Elena and Oh, Hans and Brunoni, Andre R. and Carvalho, Andre F. and Radua, Joaquim and An, Suk Kyoon and Namkoong, Kee and Lee, Eun and Shin, Jae Il and Fusar-Poli, Paolo (2021) Impact of data extraction errors in meta-analyses on the association between depression and peripheral inflammatory biomarkers: An umbrella review. Psychological Medicine. ISSN 1469-8978

[img] Text
Accepted Version
Restricted to Repository staff only until 9 May 2022.
Available under the following license: Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Request a copy
[img] Text (Word version)
Accepted Version
Restricted to Repository staff only until 9 May 2022.
Available under the following license: Creative Commons Attribution Non-commercial No Derivatives.

Download (3MB) | Request a copy
Official URL: https://doi.org/10.1017/S0033291721003767

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.

Item Type: Journal Article
Keywords: data extraction error, depression, Inflammatory biomarkers, meta-analysis, umbrella review
Faculty: Faculty of Science & Engineering
SWORD Depositor: Symplectic User
Depositing User: Symplectic User
Date Deposited: 03 Sep 2021 13:10
Last Modified: 15 Nov 2021 12:29
URI: https://arro.anglia.ac.uk/id/eprint/706896

Actions (login required)

Edit Item Edit Item