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Record W3028870049 · doi:10.1177/0844562120927535

A Cross-Sectional Exploration of Cytokine–Symptom Networks in Breast Cancer Survivors Using Network Analysis

2020· article· en· W3028870049 on OpenAlex
Ashley M. Henneghan, Michelle L. Wright, Garrett Bourne, Adam Sales

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Nursing Research · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer-related cognitive impairment studies
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Nursing ResearchAmerican Cancer Society
KeywordsLonelinessMedicinePsychologyDementiaClinical psychologyOncologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to (a) visualize the symptom–cytokine networks (perceived stress, fatigue, loneliness, perceived cognitive impairment, daytime sleepiness, sleep quality, and 13 cytokines) and (b) explore centrality metrics of symptom–cytokine networks in breast cancer survivors who completed chemotherapy treatment. Methods Cross-sectional analysis of data collected from 66 breast cancer survivors who were on average three years post chemotherapy completion. Perceived stress, fatigue, loneliness, perceived cognitive impairment, daytime sleepiness, and sleep quality were measured with self-report instruments, and a panel of 13 cytokines was measured from serum using multiplex assays. Symptoms and cytokines were simultaneously evaluated with correlations, network analysis, and community analysis. Results Network analysis revealed the nodes with the greatest degree and closeness were interleukin-2, granulocyte-macrophage colony-stimulating factor, interleukin-13, and perceived cognitive impairment. Node betweenness was highest for perceived cognitive impairment and interleukin-2. Community analysis revealed two separate communities of nodes within the network (symptoms and the cytokines). Several edges connected the two communities including perceived cognitive impairment, stress, fatigue, depression, interleukin-2, granulocyte-macrophage colony-stimulating factor, interleukin-8, interleukin-13, and interleukin-10. Partial correlation analyses revealed significant negative relationships between interleukin-2 and fatigue, loneliness, stress, and perceived cognitive impairment ( rs = −.27 to −.37, ps < .05) and a significant negative relationship between perceived cognitive impairment and granulocyte-macrophage colony-stimulating factor ( r = −.34, p < .01). Conclusions Our analyses support that perceived cognitive impairment, stress, loneliness, depressive symptoms, and fatigue co-occur and extend the literature by suggesting that interleukin-2 may contribute to the underlying mechanistic pathway of these co-occurring symptoms. Our findings add to a growing body of literature that is shifting to study symptoms as they co-occur, or cluster, rather than individual symptoms.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.156
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.158
GPT teacher head0.434
Teacher spread0.276 · 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