Symptom severity, specialty palliative care, and subsequent symptom control among adolescents and young adults with cancer: A population-based study.
Notice bibliographique
Résumé
e24127 Background: Adolescents and young adults (AYA) with cancer can suffer from substantial symptom burdens. Specialty palliative care (SPC) is recommended but often uninvolved or involved late. In a population-based AYA cohort, we determined: 1) whether symptom severity measured by routine patient report was associated with subsequent SPC involvement; and 2) whether SPC involvement was associated with subsequent symptom improvement. Methods: All Ontario, Canada AYA diagnosed with cancer aged 15-29 between 2010-2018 were identified and linked to healthcare databases, including one capturing self-reported Edmonton Symptom Assessment System (ESAS) scores at cancer-related visits. SPC was identified through validated algorithms using PC fee codes billed by SPC physicians. ESAS scores were categorized as not measured, mild (0-3), moderate (4-6), or severe (7-9), and could vary over time. For each symptom, the association of ESAS score with subsequent SPC involvement was determined, adjusting for patient and disease characteristics. For objective #2, only AYA who died within 5 years of cancer diagnosis were included and a “difference-in-difference” approach was used. Cases (SPC involvement before death, index date was time of first SPC service) were matched 1:1 to controls (no SPC involvement at equivalent index date, defined by time prior to death) by sex and cancer type. By symptom type, linear regression determined whether the difference between the 90-day post-index and 90-day pre-index mean ESAS scores was itself different between cases and controls through examining interaction terms. Results: 5,435 AYA met inclusion criteria. 5-year cumulative incidence of SPC involvement was 19% [95th confidence interval (95CI) 18-20%]. For all symptoms, moderate and severe scores were associated with increasing likelihood of SPC involvement compared to mild scores; not being ESAS screened was associated with decreased likelihood. The greatest magnitude of association was seen for pain scores [adjusted hazard ratio of SPC involvement for severe vs. mild 7.7, 95CI 5.8-10.2, p < 0.001]. 721 (13.3%) AYA died within 5 years of diagnosis; 612 (84.9%) had at least one SPC visit prior to death. 202 case-control pairs were identified. SPC involvement was associated with improved pain score trajectories (mean pain scores improved from 3.4 to 3.1 in cases vs. worsened from 1.9 to 2.1 in controls; p = 0.003), but did not impact trajectories of other symptoms. Conclusions: AYA reporting moderate or severe symptoms through a provincial screening program were more likely to subsequently receive SPC; systematic screening may increase access. SPC was associated with a subsequent decrease in pain severity, but did not affect other symptoms. New interventions targeting these other symptoms during cancer treatment and particularly at the end-of-life are urgently needed.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».