Impact of time to relapse (TTR) and metastasectomy (MTS) on survival in leiomyosarcoma (LMS): A CanSaRCC study.
Notice bibliographique
Résumé
11567 Background: Approximately 40% of LMS patients (pts) experience relapse despite standard care of surgical resection ± radiotherapy. Upon relapse, pts with advanced disease receive palliative systemic therapy. Often reserved for pts with oligometastatic disease, the role of MTS remains unclear due to a lack of randomized trials. Longer time from curative surgery to relapse (TTR) is associated with better outcomes in LMS pts who undergo MTS but its prognostic value has not been established in those treated without MTS. This study evaluates the effect of TTR on outcomes in LMS pts with metachronous metastases treated with systemic therapy ± surgery. Methods: This real-world study included advanced LMS pts treated at 4 Canadian sarcoma centers (2010–2022) who underwent curative resection, subsequent relapse, and systemic treatment ± MTS. Data were retrieved from the ethics-approved Canadian Sarcoma Research and Clinical Collaboration (CanSaRCC) database. Primary and secondary endpoints were overall survival (OS) stratified by TTR (< 6 vs ≥6 months from the completion of curative resection); and MTS, respectively. Exploratory analysis evaluated the impact of MTS in pts with low disease burden at relapse ( < 2 sites). Kaplan-Meier survival analysis and log-rank tests were used to compare OS, and Cox proportional hazards models identified independent predictors, with p < 0.05 considered significant. Results: A total of 113 pts (median age 56y) were included. Median follow-up was 38.4 months (mo). Majority (n = 93, 82%) were female and 38 (34%) had uterine leiomyosarcoma (uLMS). Relapse occurred in 109 pts (96%) with 73/109 pts (70%) having < 2 metastatic sites at relapse. TTR was < 6 months (TTR < 6) in 31/109 pts (28%) and 43/109 pts (39%) underwent MTS. Pts with TTR ≥6 months (TTR≥6) had significantly longer median OS (mOS) than those with TTR < 6 (32.9 vs 15.6mo, p = 0.006). Metastasectomy was associated with a significantly longer mOS in the whole cohort (50.4 vs 17.6mo, p < 0.0001) as well as the subgroup of patients with < 2 metastatic sites at relapse (50.6 vs 15.6mo, p < 0.0001). The mOS was 50.4 vs 24.7mo in pts with TTR≥6 who underwent MTS and those who did not, respectively (p < 0.0001). Among pts with TTR < 6 who had MTS, median OS was 44.8mo compared with 9.4mo in pts without surgery (p = 0.005). No other variables (e.g., tumor grade, primary site, metastatic burden, gender, or age) impacted OS. Both MTS (HR 0.26, 95% CI 0.16-0.49, p = 0.000) and TTR ≥ 6 (HR 0.55, 95% CI 0.33-0.91, p = 0.02) remained independent predictors of favorable OS in multivariate analysis. Conclusions: TTR≥6 was associated with longer OS in LMS pts. OS improved significantly with MTS, particularly in pts with longer TTR, though those with TTR < 6 also benefited to a lesser extent. These results underscore the role of MTS as part of an individualized treatment strategy to optimize outcomes in advanced LMS.
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) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».