Prevalence of pain symptoms among U.S. adult cancer survivors.
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».