A population-based study of health care system factors associated with receipt of treatment and treatment intent in stage III non-small cell lung cancer.
Notice bibliographique
Résumé
146 Background: Stage III non-small cell lung cancer (NSCLC) is a disease with a spectrum of anatomic extent, patient health status, and treatment approaches. When health care quality is optimal, receipt of treatment and its intent should be independent of health system factors. We investigated whether modifiable health care system-level factors are associated with receipt of treatment and treatment intent in stage III NSCLC. Methods: This was a population-based, retrospective cohort study using health administrative data covering nearly the whole population of Ontario, Canada (15 million) from 2010-2018 for people with AJCC 7 or 8 stage III NSCLC aged ≥20 years. System factors were: treatment era, diagnostic interval, health region of residence, travel distance, and volume of advanced radiotherapy and systemic therapy. The health region is responsible for administering regional cancer care. The relative risk (RR) of (1) any treatment versus no treatment, and (2) palliative-intent versus curative-intent treatment was determined, using multivariable Poisson regression models. We adjusted for patient, disease, and treatment factors, including age, sex, rurality, income quintile, substage, comorbidity, histology, and use of PET imaging. Results: 7,093 people with stage III NSCLC diagnosed between 2010 and 2018 were identified. There were differences between groups in patient, disease, and treatment factors. For example, factors associated with no treatment include advanced age (e.g. adjusted RR [95% confidence interval]: 80+ vs. 20-64, 0.83 [0.80-0.87]), greater Elixhauser comorbidity score (e.g. 3+ vs. 0, 0.88 [0.84-0.92]), dementia (RR: 0.78 [0.70-0.87]), palliative care consultation (RR: 0.92 [0.89-0.94]) and geriatrics consultation (RR: 0.82 [0.71-0.95]) (all p<0.05). On multivariable stepwise analysis adjusting for these factors, no system factors were associated with receipt of treatment versus no treatment. For those treated, patient, disease, and treatment factors associated with palliative intent were similar. Over time, there was increasing utilization of immunotherapy and advanced radiotherapy (e.g., VMAT, IMRT) (treatment eras: 2010-2012 vs. 2013-2015 vs. 2016-2018). The major system factor associated with palliative intent treatment amongst those treated was health region of residence (RR: ranges from 0.88 to 1.67, p<0.001), which remained after stratifying analysis by treatment era. Conclusions: Even with increasing adoption of advanced radiotherapy and systemic therapy over time, health region of residence emerged as the major health system-level factor associated with choice of treatment intent for stage III NSCLC after adjusting for patient, disease, and treatment factors. Our study suggests possible opportunities to improve care outcomes by addressing unexplained regional variation in care.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,000 | 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 tête enseignante, 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 ».