Survival outcomes of metastatic renal cell carcinoma (mRCC) with sarcomatoid differentiation (SD): A single-institutional experience and literature meta-analysis.
Notice bibliographique
Résumé
332 Background: Patients (pts) with mRCC with SD have unfavorable outcomes and poor prognosis due to aggressive tumor behavior. Chemotherapy and targeted treatment are often of little benefit. However, recent studies have shown a survival benefit of immunotherapy (IO). Here, we report survival outcomes of pts with mRCC with SD treated with first line IO or chemotherapy or targeted treatment. In addition we performed a meta-analysis of recent practice changing phase III, IO trials in mRCC. Methods: This retrospective survival analysis was performed in pts with mRCC with SD treated with IO or non-IO treatment at Princess Margaret Cancer Centre (PM), Toronto. Demographics, disease characteristics and survival outcomes were collected. Progression free survival (PFS), and overall survival (OS) were calculated using the Kaplan-Meier method (log-rank). PFS and OS hazard ratios (HR) were calculated using cox proportional hazards model. We identified the major, practice changing clinical trials that reported survival outcomes of mRCC with SD treated with IO and performed a random-effects meta-analysis of HR for PFS and OS. We compared these pooled results to our single institution experience. Results: We identified 474 pts diagnosed with mRCC at PM between 2002 and 2019. In total, 44 (9.3%) pts had mRCC with SD who were treated with IO or non-IO. Of these, 29 (65.9%) pts had pure SD and 15 (34.1%) pts had mixed rhabdoid and SD features. Median age was 59.6 years (36-78) and 33 (75%) were male. Overall, as per the IMDC score, 3(6.8%), 21(47.7%) and 20(45.5%) pts were categorized as good, intermediate, and poor risk, respectively. Eight (18.2%) pts were treated with IO as first line of treatment, and 36 (81.8%) pts received non-IO. With a median follow up of 64.8 months (range, 45.7-83.8 months), the median OS for the whole mRCC with SD cohort was 15.6 months (95% CI: 8.6-22.5). The median OS in all pts treated with IO vs non-IO was not reached vs 10.3 months (95%CI: 1.49-19.1 months; p = 0.005), respectively. The HR for OS was 0.1 (95%CI: 0.01-0.78; p = 0.023) favoring IO receipt. The median PFS in all pts treated with IO vs non-IO was 24 months (95%CI: non-estimable) vs 5.4 months (95%CI: 2.9-7.8 months; p = 0.021), respectively. The HR for PFS was 0.3 (95%CI: 0.11-0.89; p = 0.03) favoring IO receipt. We identified through meta-analysis five phase III clinical trials reporting PFS and OS in pts with mRCC with SD who received IO. The overall HR for OS and PFS for the total cohort were 0.55 (95%CI: 0.41-0.74), and 0.53 (95%CI: 0.42-0.67), respectively. Conclusions: Our meta-analysis has confirmed the benefit of IO agents in mRCC with SD. While the numbers included in this retrospective review were small, they have provided real world corroboration of the trial findings. Pts with mRCC and SD benefit from IO treatment, which should be considered the standard of care for these patients.
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 | 0,019 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,028 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 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 ».