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Replication and reproducibility issues in the relationship between C-reactive protein and depression: A systematic review and focused meta-analysis.


ABSTRACT: One of the most common inflammatory markers examined in depression is C-reactive protein (CRP). However, the magnitude of the association between CRP and depression when controlling for potentially confounding factors such as age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, is unclear. Inconsistencies in other methodological practices, such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. We aggregate studies that examined the association between CRP and depression in two ways. First, a systematic review summarizes how studies of CRP and depression have reported on methodological issues. Second, a tiered meta-analysis aggregates studies that have adhered to various levels of methodological rigor. Findings from the systematic review indicate a lack of protocol detail provided. The effect between depression and CRP was small, but highly significant across all stages of the meta-analysis (p?

SUBMITTER: Horn SR 

PROVIDER: S-EPMC6800199 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Replication and reproducibility issues in the relationship between C-reactive protein and depression: A systematic review and focused meta-analysis.

Horn Sarah R SR   Long Madison M MM   Nelson Benjamin W BW   Allen Nicholas B NB   Fisher Philip A PA   Byrne Michelle L ML  

Brain, behavior, and immunity 20180619


One of the most common inflammatory markers examined in depression is C-reactive protein (CRP). However, the magnitude of the association between CRP and depression when controlling for potentially confounding factors such as age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, is unclear. Inconsistencies in other methodological practices, such as sample collection, assaying, and data cleaning and transformation, may contribute to variations  ...[more]

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