Outcomes of larotrectinib compared with real-world data from non-TRK inhibitor therapies in patients with TRK fusion cancer: VICTORIA study.
Notice bibliographique
Résumé
3105 Background: NTRK gene fusions are oncogenic drivers identified in <1% of solid tumors. Larotrectinib (laro) is a highly selective TRK inhibitor (i) that was approved in patients (pts) with TRK fusion cancers based on data from single-arm trials. Here we report results from VICTORIA (NCT05192642), a protocol-driven, exact-matching study comparing the outcomes of pts with TRK fusion cancer treated with laro in clinical trials (NCT02122913, NCT02576431, NCT02637687) to pts treated with non-TRKi therapies in the real-world (RW) setting. Methods: Adult (≥18 years old) pts with non-small cell lung cancer, colorectal cancer, soft-tissue sarcoma, thyroid cancer, or salivary gland carcinoma were included. Deduplicated data from RW pts were from US and ex-US databases: American Association for Cancer Research GENIE, Cardinal, Flatiron, and ORIEN, as well as a global chart review. Pts in the laro cohort were exactly matched to RW pts based on tumor type and line of therapy to define index line and date for RW pts. A propensity score (weighting) model was used to balance key pt characteristics between cohorts. Pts were followed from index date to last activity, end of study period, or death, whichever occurred first. RW pts were censored at the start of any TRKi therapy or investigational agent, or censored at their last known alive date. Overall survival (OS) was the primary outcome. Results: In total,164 pts with TRK fusion cancer were matched (82 in each cohort). Balance in the baseline covariates was achieved after weighting. Matched RW pts received standard index treatments for their disease, which comprised chemotherapy (49%), non-TRKi small molecule targeted therapy (27%), chemotherapy + non-TRKi non-small-molecule targeted therapy (11%), or immune checkpoint inhibitor therapy (10%). Laro-treated pts had longer OS compared to RW pts (median not reached [NR] vs 37.2 months; hazard ratio [HR]: 0.44 [95% confidence interval {CI}: 0.23-0.83]) after weighting. In the weighted analysis, laro-treated pts had longer time to next therapy (TTNT; median NR vs 10.6 months; HR: 0.22 [95% CI: 0.13-0.38]), duration of therapy (DoT; median 30.8 vs 3.4 months; HR: 0.23 [95% CI: 0.15-0.33]), and progression-free survival (PFS; median 36.8 vs 5.2 months; HR: 0.29 [95% CI: 0.18-0.46] compared to RW pts. Conclusions: In adult pts with TRK fusion cancer, treatment with laro was associated with longer OS and all measured time-to-event endpoints (TTNT, DoT, and PFS), compared to exactly matched pts treated with standard non-TRKi therapies in the RW. These results furnish additional evidence illustrating the benefit of laro treatment in pts with TRK fusion cancer and support the data generated in the single-arm registrational trials. Clinical trial information: NCT05192642 .
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 | 0,004 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| 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 ».