Sequencing of systemic therapies in advanced NSCLC with <i>MET</i> exon 14 skipping mutation: A multicenter experience.
Notice bibliographique
Résumé
e21123 Background: The treatment landscape for patients with metastatic non-small cell lung cancer (mNSCLC) with a MET exon 14 skipping mutation ( MET ex14) is rapidly changing, with recent approvals of MET selective tyrosine kinase inhibitors (TKIs) and reports of durable response to immune checkpoint inhibitors (ICI), particularly among those with sarcomatoid histology. Currently there are no published data that inform the sequencing of TKIs and ICI regimens. We sought to characterize treatment patterns and outcomes in this population at 3 Ontario cancer centres. Methods: We reviewed all mNSCLC patients with MET ex14 identified by tissue or plasma NGS in the last 4 years. Patients with EGFR co-mutation or MET amplification alone were excluded. All systemic therapies and outcomes of overall response (ORR), progression free survival (PFS), overall survival (OS), and adverse events (AEs) were captured. Results: We identified 43 patients with MET alterations, of whom 29 had MET ex14: median age 73 years (54-92), 66% female, 79% non-smokers. Tumor histology was adenocarcinoma in 76%, pleomorphic/sarcomatoid in 21% and adenosquamous in 3% of patients. 69% of patients had PD-L1 ≥50%. At presentation, 20% of patients had high disease burden and ECOG ≥2. Among 15 patients who received ICI, ORR with ICI monotherapy was 45% (10/11 had PD-L1 ≥50%) and ORR with ICI plus chemotherapy was 75% (4/4 had PD-L1 0-49%). Responses were seen in 50% of non-smokers (7/12 had PD-L1 ≥50%). The median PFS with ICI was 10.6 months (1.7-NR). MET TKIs were received by 18 patients (16 crizotinib, 1 capmatinib, 1 cabozantinib), with an ORR of 28% (30% amongst those who received crizotinib first line). The median PFS with TKIs was 2.6 months (1.2-8.9). Median OS for the entire cohort was 24.4 months (10.1-48.3). Patients who received initial ICI (n = 13) compared to those who received initial TKI (n = 11) had significantly longer OS (48.3 vs 13.6 months; p = 0.005), not controlled for prognostic factors. All patients who progressed after ICI (9/13) received further treatment while only 50% of patients who progressed after TKI (8/11) received subsequent therapy. 7 patients received TKI therapy after ICI with a median time to TKI of 35 days (24-181). 6 patients (85.7%) experienced an early grade ≥3 AE (4 transaminitis, 2 pneumonitis) resulting in permanent discontinuation of TKI in half of patients. There were no treatment-related deaths. Conclusions: Patients with MET ex14 NSCLC benefit from ICI irrespective of PD-L1 expression and smoking history. ORR and PFS with earlier generation TKIs (crizotinib) were poor. Increased toxicity is seen when a TKI is used after ICI and careful monitoring is necessary. Future studies focusing on the optimal sequencing of TKIs and ICI-containing therapy should be prioritized, as well as broader access to newer generation MET TKIs with greater activity.
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 | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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) | 0,001 | 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 ».