P648: REAL-WORLD TREATMENT AND OUTCOMES OF PATIENTS WITH CHRONIC LYMPHOCYTIC LEUKEMIA (CLL) RECEIVING FIRST-LINE (1L) THERAPY IN THE NOVEL AGENT ERA: AN INTERNATIONAL STUDY
Notice bibliographique
Résumé
Background: An expansion of treatment options in CLL makes it important to understand contemporary practice and treatment effectiveness. However, real-world data are still emerging regarding outcomes among different therapeutic options. Aims: The study goal was to describe treatment patterns and clinical outcomes of patients (pts) receiving 1L CLL treatment in real-world settings. Methods: Twenty three centers of the CLL Collaborative Study of Real-World Evidence (CORE), an international, retrospective, observational study, provided data for this analysis. Pts diagnosed with CLL/SLL were included if they were ≥18 years at diagnosis and initiated 1L therapy on/after 01/01/2014 and excluded if they participated in a clinical trial. Descriptive analyses were conducted to characterize pt demographics and clinical characteristics. Outcomes, including time to next treatment or death (TTNT-D) and progression-free survival (PFS), were estimated via the Kaplan-Meier (KM) method for the overall population and those with high-risk cytogenetics (del(17p)/TP53 and IGHV unmutated) or age ≥65. Results: Of 1,244 pts included in the study, between 2014-2022, 39% initiated CT/CIT in 1L (eg, bendamustine-rituximab [BR, 16%]; fludarabine-cyclophosphamide-rituximab [FCR, 9%]; obinutuzumab-chlorambucil [GClb, 5%]), 9% anti-CD20 monotherapy (eg, rituximab, 6%; obinutuzumab, 2%), 45% BTKi-based therapy (eg, ibrutinib, 42%; acalabrutinib, 3%), 7% venetoclax (Ven)-based therapy (eg, venetoclax-obinutuzumab [V+G, 5%]; venetoclax-rituximab [V+R, 1%]; venetoclax monotherapy, 1%), and 1% initiated other therapies over a median follow-up of 13-34 months. The median age was 63 years at diagnosis and 66 years at 1L initiation; 66% of pts were males, 35% had unmutated IGHV, and 15% had del(17p)/TP53, though 32-53% were not tested for IGHV and 10-18% for genetic mutations. Overall, the median TTNT-D (mTTNT-D) was 35, 18, 43 months for pts who received 1L therapy with CT/CIT, anti-CD20, and BTKi, respectively; mTTNT-D was not reached for Ven-based therapy over a median follow-up of 13 months. KM estimates of TTNT-D at month 24 were 64%, 42%, 69%, and 88% for CT/CIT, anti-CD20, BTKi, and Ven-based therapy, respectively (Table1). Trends were similar in subgroups: del(17p)/TP53, IGHV unmutated, or age ≥65. The median PFS (mPFS) was 39, 23, 51 months for pts who received CT/CIT, anti-CD20, and BTKi, respectively; mPFS was not reached for Ven-based therapy. KM estimates of PFS at month 24 were 67%, 48%, 80%, and 88% for CT/CIT, anti-CD20, BTKi- and Ven-based therapy, respectively (Table1). Similar trends were seen in subgroups: del(17p)/TP53, IGHV unmutated, or age ≥65. Patients categorized into the ‘other’ treatment group were not assessed due to low sample size (n=11; 1%).Summary/Conclusion: Our study presents contemporary practice and outcomes in CLL. We observed that almost 50% of pts were treated in the front-line setting with anti-CD20 monotherapy or CT/CIT despite availability of targeted agents. The continued use of anti-CD20 monotherapy and CT/CIT is surprising in the era of novel agents. Pts initiating 1L therapy with anti-CD20 or CT/CIT experienced worse clinical outcomes, providing further evidence of the effectiveness afforded by novel agents in 1L. Although mTTNT-D and mPFS were not reached for Ven-based therapy perhaps due to shorter follow-up, KM estimates tended to be higher through month 24, especially for high-risk and older pts. As the treatment paradigm continues to evolve, future exploration with larger cohorts and longer follow-up time should be undertaken. Keywords: Progression, Chemotherapy, Targeted therapy, Clinical outcome
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 ».