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Record W4301205140

Cytokines and depression in cancer patients and caregivers

2017· article· en· W4301205140 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)CancerMedicinePsychologyOncologyPsychiatryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Madeline Li,1,2 Ekaterina Kouzmina,3 Megan McCusker,1 Danielle Rodin,4 Paul C Boutros,3,5,6 Christopher J Paige,6–8 Gary Rodin1,2 1Princess Margaret Cancer Centre, Department of Supportive Care, University Health Network, Toronto, Ontario, Canada; 2Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; 3Informatics & Biocomputing Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada; 4Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; 5Department of Pharmacology & Toxicology, Toronto, Ontario, Canada; 6Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; 7Department of Immunology, University of Toronto, Toronto, Ontario, Canada; 8Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada Objective: A better understanding of the biobehavioral mechanisms underlying depression in cancer is required to translate biomarker findings into clinical interventions. We tested for associations between cytokines and the somatic and psychological symptoms of depression in cancer patients and their healthy caregivers.Patients and methods: The GRID Hamilton Rating Scale for Depression (Ham-D) was administered to 61 cancer patients of mixed type and stage, 26 primary caregivers and 38 healthy controls. Concurrently, blood was drawn for multiplexed plasma assays of 15 cytokines. Multiple linear regression, adjusted for biobehavioral variables, identified cytokine associations with the psychological (Ham-Dep) and somatic (Ham-Som) subfactors of the Ham-D.Results: The Ham-Dep scores of cancer patients were similar to their caregivers, but their Ham-Som scores were significantly higher (twofold, p=0.016). Ham-Som was positively associated with IL-1ra (coefficient: 1.27, p≤0.001) in cancer patients, and negatively associated with IL-2 (coefficient: -0.68, p=0.018) in caregivers. Ham-Dep was negatively associated with IL-4 (coefficient: -0.67, p=0.004) in cancer patients and negatively associated with IL-17 (coefficient: -1.81, p=0.002) in caregivers.Conclusion: The differential severity of somatic symptoms of depression in cancer patients and caregivers and the unique cytokine associations identified with each group suggests the potential for targeted interventions based on phenomenology and biology. The clinical implication is that depressive symptoms in cancer patients can arise from biological stressors, which is an important message to help destigmatize the development of depression in cancer patients. Keywords: depression, psychological symptoms, somatic symptoms, cytokines, cancer, caregiver

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.208
GPT teacher head0.523
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
Admission routes1
Has abstractyes

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