Efficacy of Savolitinib vs Sunitinib in Patients With<i>MET</i>-Driven Papillary Renal Cell Carcinoma
Notice bibliographique
Résumé
Importance: Papillary renal cell carcinoma (PRCC) is the most common type of non-clear cell RCC. Because some cases of PRCC are MET-driven, MET inhibition could be a targeted treatment approach. In previous studies, savolitinib (AZD6094, HMPL-504, volitinib), a highly selective MET-tyrosine kinase inhibitor, demonstrated antitumor activity in this patient group. Objective: To determine whether savolitinib is a better treatment option for this patient population, vs standard of care, sunitinib. Design, Setting, and Participants: The SAVOIR phase 3, open-label, randomized clinical trial was a multicenter study carried out in 32 centers in 7 countries between July 2017 and the data cutoff in August 2019. Overall, 360 to 450 patients were to be screened to randomize approximately 180 patients. Patients were adults with MET-driven (centrally confirmed), metastatic PRCC, with 1 or more measurable lesions. Exclusion criteria included prior receipt of sunitinib or MET inhibitor treatment. Overall, 254 patients were screened. Interventions: Patients received 600 mg of savolitinib orally once daily (qd), or 50 mg of sunitinib orally qd for 4 weeks, followed by 2 weeks without treatment. Main Outcomes and Measures: The primary end point was progression-free survival (PFS, assessed by investigator and confirmed by blinded independent central review). Secondary end points included overall survival (OS), objective response rate (ORR), duration of response, and safety/tolerability. Results: At data cutoff, 60 patients were randomized (savolitinib n = 33; sunitinib n = 27); most patients had chromosome 7 gain (savolitinib, 30 [91%]; sunitinib, 26 [96%]) and no prior therapy (savolitinib, 28 [85%]; sunitinib, 25 [93%]). For savolitinib and sunitinib, 4 (12%) and 10 (37%) patients were women, and the median (range) age was 60 (23-78) and 65 (31-77) years, respectively. Following availability of external data on PFS with sunitinib in patients with MET-driven disease, study enrollment was closed. Progression-free survival, OS, and ORR were numerically greater with savolitinib vs sunitinib. Median PFS was not statistically different between the 2 groups: 7.0 months (95% CI, 2.8-not calculated) for savolitinib and 5.6 months (95% CI, 4.1-6.9) for sunitinib (hazard ratio [HR], 0.71; 95% CI, 0.37-1.36; P = .31). For savolitinib and sunitinib respectively, grade 3 or higher adverse events (AEs) were reported in 14 (42%) and 22 (81%) of patients and AE-related dose modifications in 10 (30%) and 20 (74%). After discontinuation, 12 (36%) and 5 (19%) of patients on savolitinib and sunitinib respectively, received subsequent anticancer therapy. Conclusions and Relevance: Although patient numbers and follow-up were limited, savolitinib demonstrated encouraging efficacy vs sunitinib, with fewer grade 3 or higher AEs and dose modifications. Further investigation of savolitinib as a treatment option for MET-driven PRCC is warranted. Trial Registration: ClinicalTrials.gov Identifier: NCT03091192.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 ».