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Prevalence of pain symptoms among U.S. adult cancer survivors.

2022· article· en· W4286294387 on OpenAlexaff
Xinwen Hu, Chao Cao, Yunan Han, Shu Jiang, Lin Yang, Graham A. Colditz

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsMedicineCancerBreast cancerPopulationPhysical therapyBack painProstate cancerInternal medicineCancer painPathology

Abstract

fetched live from OpenAlex

12062 Background: Pain symptoms are common in cancer survivors. The life expectancy of US cancer survivors continues to raise. To date, the comprehensive pattern of pain symptoms in US cancer survivors by cancer history remains unknown. Methods: Data on pain symptoms and correlates were derived from a nationally representative sample of cancer survivors (n = 55,716, weighted population = 17,352,886) in the 1997-2018 National Health Interview Survey. Individuals who answered “yes” to the questions “During the past three months, did you have headache/facial/neck/low back pain/low back pain radiating to the leg” were considered as having pain symptoms at respective anatomical regions. The US national prevalence of pain overall and by anatomical regions were estimated. Correlates of pain symptoms were examined using multivariable logistic regression. Results: The prevalence of overall pain symptoms was persistently high (48.5%, 95% CI: 48.0-49.0) in cancer survivors from 1997-2018 ( P for trend =.58), driven by low back (37.6%, 95% CI: 37.1-38.0) and neck pain (20.9%, 95% CI: 20.5-21.3), and was leading in survivors of bone (63.1%, 95% CI: 57.9-68.4), soft tissue (58.1%, 95% CI: 50.6-65.6), and brain (58.2%, 95% CI: 52.3-64.0) cancers. Considerable pain symptoms were reported by survivors of commonly diagnosed cancers: lung (48.5%), breast (46.7%), colon (52.2%) and prostate (38.4%) cancers. The prevalence of pain is higher in females (52.9%) than males (42.6%) across all anatomical regions (OR, 1.50 [95% CI, 1.38-1.63]), particularly headache (19.8% vs. 8.6%) and facial pain (8.6% vs. 3.9%). Of note, females with reproductive system cancers, cervical (66.3%), uterine (60.0%) and ovarian (59.4%) cancers, have a higher prevalence in all types of pain than those with other cancers. Cancer survivors aged ≥65 years were less likely to report pain symptoms than younger survivors (OR, 0.71 [95% CI, 0.64-0.79]). Despite no racial disparity in the prevalence of overall pain, Non-Hispanic Blacks (18.6%, 95% CI: 17.2-20.0) and Hispanics (21.2%, 95% CI: 19.5-22.9) were more likely to report headache than Non-Hispanic Whites (14.4%, 95% CI: 14.0-14.8). A higher prevalence of pain symptoms was consistently observed in cancer survivors with low income, smoking history, low physical activity levels, diabetes, and cardiovascular diseases (all P <.05). Age at cancer diagnosis ( P for trend <.001), but not the time since, affected pain symptoms. Cancer survivors diagnosed at age 0-14 (53.0%, 95% CI: 49.1-56.9) and 15-39 years (58.6%, 95% CI: 57.5-59.7) had a significantly higher prevalence of pain across all anatomical regions than those at ≥40 years (45.5%, 95% CI: 44.9-46.1). Conclusions: Half of US cancer survivors experienced pain symptoms, driven by low back and neck pain. Higher prevalence of pain was noted in cancer survivors with younger age, female sex, low income and suboptimal lifestyle behaviors, calling for adequate pain management in cancer survivorship.

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)0.002
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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.437
Teacher spread0.370 · 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
Published2022
Admission routes1
Has abstractyes

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