Trends and disparities in the treatment of older adults with colon cancer.
Notice bibliographique
Résumé
e18776 Background: Adults aged ≥70 years represent approximately half of all patients diagnosed with colon cancer (CC), but undertreatment in this population persists. Recent guidelines have aimed to reduce age-related biases in the treatment of CC and emphasized the importance of personalizing management with comprehensive geriatric assessments (CGAs). Therefore, we hypothesized that age-related disparities in the curative-intent treatment of CC would improve over time. Methods: This was a retrospective, population-based cohort study of adults diagnosed with CC between 2010 and 2018 in Alberta, Canada. The study data included patient demographics and clinical characteristics collected through the Alberta Cancer Registry and electronic medical records. Patients were stratified by age: < 70 and ≥70 years. Cox proportional hazard models (CPHM) were generated to evaluate the associations and interaction between age groups and treatment status on disease-specific survival (DSS), after adjusting for important covariates. Multivariable logistic regression was used to identify time trends and predictors of treatment receipt. Results: A total of 10,838 patients were included, of whom 5,176 (48%) were aged ≥70 years and 2,468 (23%) had stage IV CC at initial diagnosis. Older age was associated with greater comorbidity and less advanced disease ( p < 0.001, standardized mean difference > 0.1 for both). The vast majority (87%) of patients in the overall cohort received surgery while 34% received systemic therapy. In multivariable CPHM, older age was associated with lower DSS (HR 1.42, 95%CI 1.31-1.54, p < 0.001) while surgery and systemic therapy were each associated with higher DSS (HR 0.30, 95%CI 0.27-0.33, p < 0.001; HR 0.40, 95%CI 0.37-0.43, p < 0.001; respectively). However, the interaction between age and treatment status was not statistically significant ( p = 0.78 for surgery; p = 0.17 for systemic therapy). Compared to the younger age group, the odds of receiving surgery and systemic therapy were 3 and 5 times lower, respectively, among older patients (OR 0.27, 95%CI 0.18-0.40, p < 0.001; OR 0.18, 95%CI 0.16-0.20, p < 0.001; respectively). In addition to younger age, predictors of surgery receipt included less comorbidity and stage II/III vs I disease, whereas predictors of systemic therapy receipt included male sex, southern residence, higher neighbourhood income, less comorbidity, and stage III vs IV disease ( p < 0.05 for all). There were no statistically significant correlations between year of diagnosis and treatment receipt ( ptrend = 0.07 for surgery; ptrend = 0.26 for systemic therapy). Conclusions: Surgery and systemic therapy continue to improve CC outcomes regardless of age. However, rates of curative-intent treatment for CC were consistently lower in patients aged ≥70 years, with minimal changes over time. Better integration of CGAs into routine care may be needed to reduce persistent age-related treatment disparities.
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 | 0,000 |
| 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 ».