Bias in peripheral depression biomarkers

Carvalho, Andre F., Köhler, Cristiano A., Brunoni, Andre R., Miskowiak, Kamilla W., Herrmann, Nathan, Lanctôt, Krista L., Hyphantis, Thomas N., Quevedo, Joao, Fernandes, Brisa S. and Berk, Michael 2016, Bias in peripheral depression biomarkers, Psychotherapy and psychosomatics, vol. 85, no. 2, pp. 81-90, doi: 10.1159/000441457.

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Title Bias in peripheral depression biomarkers
Author(s) Carvalho, Andre F.
Köhler, Cristiano A.
Brunoni, Andre R.
Miskowiak, Kamilla W.
Herrmann, Nathan
Lanctôt, Krista L.
Hyphantis, Thomas N.
Quevedo, Joao
Fernandes, Brisa S.ORCID iD for Fernandes, Brisa S.
Berk, MichaelORCID iD for Berk, Michael
Journal name Psychotherapy and psychosomatics
Volume number 85
Issue number 2
Start page 81
End page 90
Total pages 10
Publisher Karger
Place of publication Basel, Switzerland
Publication date 2016
ISSN 1423-0348
Keyword(s) major depressive disorder
Science & Technology
Social Sciences
Life Sciences & Biomedicine
Summary BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect sizes has been conducted. METHODS: Here, we performed a comprehensive review of meta-analyses of peripheral nongenetic biomarkers that could discriminate individuals with MDD from nondepressed controls. PubMed/MEDLINE, EMBASE, and PsycINFO databases were searched through April 10, 2015. RESULTS: From 15 references, we obtained 31 eligible meta-analyses evaluating biomarkers in MDD (21,201 cases and 78,363 controls). Twenty meta-analyses reported statistically significant effect size estimates. Heterogeneity was high (I2 ≥ 50%) in 29 meta-analyses. We plausibly assumed that the true effect size for a meta-analysis would equal the one of its largest study. A significant summary effect size estimate was observed for 20 biomarkers. We observed an excess of statistically significant studies in 21 meta-analyses. The summary effect size of the meta-analysis was higher than the effect of its largest study in 25 meta-analyses, while 11 meta-analyses had evidence of small-study effects. CONCLUSIONS: Our findings suggest that there is an excess of studies with statistically significant results in the literature of peripheral biomarkers for MDD. The selective publication of 'positive studies' and the selective reporting of outcomes are possible mechanisms. Effect size estimates of meta-analyses may be inflated in this literature.
Language eng
DOI 10.1159/000441457
Field of Research 110319 Psychiatry (incl Psychotherapy)
1701 Psychology
Socio Economic Objective 920410 Mental Health
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, S. Karger AG, Basel
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Document type: Journal Article
Collections: Faculty of Health
School of Medicine
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