Abstract P4-01-42: Pooled analysis of post-progression treatments after first-line ribociclib + endocrine therapy in patients with HR+/HER2− advanced breast cancer in the MONALEESA-2, -3, and -7 studies
Notice bibliographique
Résumé
Abstract Background: The MONALEESA (ML) studies showed significant PFS & OS benefits for 1L ribociclib (RIB) + endocrine therapy (ET) in patients (pts) with pre/peri & postmenopausal advanced breast cancer. The benefit of RIB beyond study treatment (tx) was also observed, with improvements in PFS2 & delays in time to 1st subsequent chemotherapy (CT). While there is currently no preferred tx for the next line post-progression on a CDK4/6 inhibitor (CDK4/6i), except alpelisib in pts with a PIK3CA mutation, guidelines encourage multiple lines of ET or ET-based therapies before switching to CT (except for visceral crisis). This pooled exploratory analysis of the ML studies examined outcomes of various tx strategies post progression on RIB + ET. Methods: Data from pts receiving 1L therapy in ML-2, -3, & -7 (NSAI cohort only & excluding pts with early relapse [≤ 12 mo after end of (neo)adjuvant ET] whose prognosis is closer to that of 2L pts) were pooled & pts receiving 1st subsequent therapies after progression were analyzed. Three groups of subsequent therapies were assessed: ET only, CT, & targeted therapy. Subsequent CT comprises CT +/- any other therapy; targeted therapy includes CDK4/6i, mTORi, PI3Ki, AKTi, etc, +/- ET. Subsequent CT & targeted therapy groups are mutually exclusive. Median duration of study tx, 1st subsequent therapy, & OS (from randomization to death) were analyzed by KM methods. Weighted Cox regressions were performed using inversed propensity scoring matching method (inverse probability tx weighting [IPTW]) to ensure compatible pt characteristics between tx arms. These are not randomized comparisons; only baseline characteristics were used for the estimation of propensity scores in the IPTW, imbalance of prognostic factors at progression may exist. Results: Median follow-up time was 74 mo. 461 pts treated with RIB (81%) & 440 (86%) with PBO discontinued study tx & received a subsequent therapy. In the RIB arms, the most common 1st subsequent therapies were ET only (40%), CT (29%), combination with targeted therapy (28%), & other (4%); for the PBO arms, 34% received CT as a 1st subsequent therapy & 31% each received ET only or combination with targeted therapy (5% received other). In 14% & 20% of pts in the RIB & PBO arms, the 1st subsequent therapy was a CDK4/6i, of these 31% & 12% were RIB. In general, regardless of type of 1st subsequent therapy, the duration of both the study tx & the 1st subsequent therapy was longer for pts treated with RIB vs PBO (Table). In both RIB & PBO arms, pts who received subsequent CT had the shortest duration on study tx, whereas those who received subsequent targeted therapy combination had the longest. Among pts on 1L RIB + ET, after matching pre-randomization baseline characteristics, subsequent CDK4/6i use was associated with the longest mOS (84 [84-NE] mo), followed by ET only (60 [51-68] mo), then a non-CDK4/6i targeted therapy (52 [43-72] mo); post-progression CT was associated with the shortest mOS (37 [32-48] mo). Conclusions: This large, pooled analysis of the ML studies shows that, in general, duration of any subsequent therapy was numerically longer post-1L RIB + ET vs PBO + ET, & subsequent CT was used less frequently for pts on RIB vs PBO. Both findings confirm that upfront tx with RIB does not worsen pt outcomes. This trend in enhancement of outcomes of subsequent therapies seen with 1L RIB suggests a post-tx effect that merits further exploration. Citation Format: Erika Hamilton, Laura M. Spring, Peter A. Fasching, Sandra Franco, Richard H DeBoer, Javier Cortés, Kevin Kalinsky, Dejan Juric, Aditya Bardia, Sina Haftchenary, Agnes Lteif, Juan Pablo Zarate, Liyi Cen, Patrick Neven. Pooled analysis of post-progression treatments after first-line ribociclib + endocrine therapy in patients with HR+/HER2− advanced breast cancer in the MONALEESA-2, -3, and -7 studies [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-01-42.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| 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) | 0,000 | 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 tête enseignante, 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 ».