Real-world practice patterns, treatment-related toxicity, and survival outcomes in older patients with metastatic renal cell carcinoma: Results from the Canadian Kidney Cancer information system (CKCis).
Notice bibliographique
Résumé
366 Background: There is a paucity of data with respect to optimal management of metastatic renal cell carcinoma (mRCC) in older adults. Real world data may help close this knowledge gap and improve care for older patients with mRCC. Methods: The Canadian Kidney Cancer information system (CKCis) was utilized to identify patients with mRCC, categorizing them as either older (defined as age ≥75 years) or younger (age <75 years). We compared first line (1L) mRCC management strategies and treatment-related toxicities. Secondary outcomes were overall survival (OS) and time to treatment discontinuation (TTD). Chi-Square and Fisher’s Exact tests were used to compare groups, and survival outcomes were measured by Kaplan-Meier method. Cox’s proportional hazard ratio (HR) were reported by age adjusting for IMDC risk groups, histology, and Charlson Comorbidity Index (CCI) for OS and TTD. Results: 2576 patients were included (n=2203 <75 years old; n=373 ≥75 years old). Baseline demographics were comparable between groups, though older patients had more comorbidities (5+, 95% vs. 67%, p<0.0001) and more frequently had Karnofsky Performance Status <70% (18% vs. 13%, p=0.01). Older patients underwent metastasectomy less frequently (15% vs. 25%, p=0.0001) and were less likely to be enrolled in clinical trials (10% vs. 24%, p<0.0001). Older patients received 1L tyrosine kinase inhibitor (TKI) monotherapy more frequently (79% vs. 69%, p<0.0001) than immune checkpoint inhibitor (ICI)-based treatment, even when adjusted by year to account for changes in practice patterns in the post-ICI era (65% vs. 44%, p<0.0001). Amongst all patients, the TKI monotherapy most frequently prescribed was sunitinib, though older patients were more likely to receive pazopanib than younger patients ( p<0.0001). Amongst all patients who received 1L ICI-based treatment, there was no difference in the type of ICI regimen (i.e. doublet ICI versus ICI plus TKI) prescribed when compared by age ( p=0.61). Older patients did not experience more frequent treatment-related toxicities with ICI-based treatment. They did however experience more grade 3+ toxicity with TKI monotherapy. Older patients had shorter OS even when controlling for IMDC score, CCI and histology (HR 1.21, 95% CI 1.03-1.43, p=0.02). There was no difference in TTD by groups. Conclusions: Patients ≥75 years of age received TKI monotherapy more frequently than those <75 years of age, though when they received ICI-based regimens, they did not experience more treatment-related toxicities nor more dose modifications. Clinicians should individualize treatments for older patients not solely based on age, but after discussion of all available options in a patient-centered manner, considering comorbidities, disease burden, and patient preferences.
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 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».