The effectiveness of a provincial symptom assessment program in reaching adolescents and young adults with cancer: A population-based cohort study.
Notice bibliographique
Résumé
12101 Background: Symptom control is prioritized by cancer patients and may improve overall survival. Several jurisdictions have thus launched population-wide initiatives to assess symptoms at regular intervals. In Ontario, Canada, for example, all cancer patients are screened using the Edmonton Symptom Assessment System (ESAS) at every outpatient visit. Few studies have examined symptom burdens in adolescents and young adults (AYA). Previous work suggests that AYA symptoms differ from those in older patients, and that general screening tools may not be appropriate. Despite this, whether current symptom screening initiatives reach AYA with cancer are unknown. We therefore determined 1) Whether AYA with cancer were participating in ESAS screening, and 2) Which AYA were at highest risk of not being screened. Methods: We identified all Ontario AYA diagnosed with cancer at age 15-29 years between 2010-2018 and treated in adult centers. Patients were linked to population-based databases to identify all cancer-related outpatient visits in the year following diagnosis and whether visits involved completion of an ESAS form. Each patient’s first year was divided into two-week periods. For each period, AYA were considered either “unscreened” if they had a cancer-related visit but no ESAS score, or “screened” if they had a cancer-related visit with at least one ESAS score. Periods without cancer-related visits were not considered, given no potential for ESAS screening during such periods. Covariates included age at diagnosis, sex, cancer type, neighbourhood income quintile, and institution type [regional cancer centre (RCC) vs. community]. Multivariable logistic regression models were implemented under a generalized estimating equations approach to account for individual-level correlation. Results: The final cohort included 5,435 AYA. Within any given two-week period, only 36-45% of AYA attending cancer-related outpatient visits were screened. In adjusted analyses, age and sex were not associated with being screened. However, AYA living in the lowest income quintile neighbourhood were less likely to be screened [odds ratio (OR) 0.86, 95th confidence interval (95CI) 0.77-0.97; p = 0.01] compared to those in the highest. Patients with hematologic malignancies were least likely to be screened (OR 0.77, 95CI 0.67-0.88; p < 0.001), as were AYA attending community centers (OR 0.48, 95CI 0.42-0.55; p < 0.001). Conclusions: Despite a population-wide symptom assessment program, only a minority of AYA are screened. Though patients with hematologic cancers suffer from particularly high symptom burdens, they were less likely to be screened. Interventions targeting AYA are required to increase uptake, particularly among those in disadvantaged neighborhoods or attending community hospitals. Studies of AYA-specific symptom assessment tools are also warranted.
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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».