Evidence map›Paper›PMID 25698954›Full record

ReviewFrontiers in human neuroscience2015

Risk assessment and predicting outcomes in patients with depressive symptoms: a review of potential role of peripheral blood based biomarkers.

Bhautesh D Jani, Gary McLean, Barbara I Nicholl, Sarah J E Barry, Naveed Sattar, Frances S Mair, Jonathan Cavanagh

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in human neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.9field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 36 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Multimorbidity.Nature reviews. Disease primers · 2022
    Review
  6. Article
  7. Animal models for the study of depressive disorder.CNS neuroscience & therapeutics · 2021
    Review
  8. Treatment-Resistant Depression Revisited: A Glimmer of Hope.Journal of personalized medicine · 2021
    Review
  9. Article
  10. Peripheral Markers of Depression.Journal of clinical medicine · 2020
    Review
  11. Article
  12. Review
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Bhautesh D JaniGeneral Practice and Primary Care, Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow Glasgow, UK.
Gary McLeanGeneral Practice and Primary Care, Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow Glasgow, UK.
Barbara I NichollGeneral Practice and Primary Care, Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow Glasgow, UK.
Sarah J E BarryRobertson Centre for Biostatistics, Institute of Health and Well Being, College of Medical, Veterinary and Life Sciences, University of Glasgow Glasgow, UK.
Naveed SattarBHF Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow Glasgow, UK.
Frances S MairGeneral Practice and Primary Care, Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow Glasgow, UK.
Jonathan CavanaghMental Health and Wellbeing, Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow Glasgow, UK.
University of Glasgow · GB

Funding

Chief Scientist Office CAF/12/04
6 · The paper itself

Abstract

Depression is one of the major global health challenges and a leading contributor of health related disability and costs. Depression is a heterogeneous disorder and current methods for assessing its severity in clinical practice rely on symptom count, however this approach is unreliable and inconsistent. The clinical evaluation of depressive symptoms is particularly challenging in primary care, where the majority of patients with depression are managed, due to the presence of co-morbidities. Current methods for risk assessment of depression do not accurately predict treatment response or clinical outcomes. Several biological pathways have been implicated in the pathophysiology of depression; however, accurate and predictive biomarkers remain elusive. We conducted a systematic review of the published evidence supporting the use of peripheral biomarkers to predict outcomes in depression, using Medline and Embase. Peripheral biomarkers in depression were found to be statistically significant predictors of mental health outcomes such as treatment response, poor outcome and symptom remission; and physical health outcomes such as increased incidence of cardiovascular events and deaths, and all-cause mortality. However, the available evidence has multiple methodological limitations which must be overcome to make any real clinical progress. Despite extensive research on the relationship of depression with peripheral biomarkers, its translational application in practice remains uncertain. In future, peripheral biomarkers identified with novel techniques and combining multiple biomarkers may have a potential role in depression risk assessment but further research is needed in this area.

Indexed as

depressionoutcomesperipheral biomarkersrisk assessmenttreatment response

Identifiers

PMID25698954
PMCPMC4313702
OpenAlexW2104345615

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.