Azacitidine (AZA) Versus Conventional Care Regimens (CCR) in Older Patients with Newly Diagnosed Acute Myeloid Leukemia (>30% Bone Marrow Blasts) with Morphologic Dysplastic Changes: A Subgroup Analysis of the AZA-AML-001 Trial
Notice bibliographique
Résumé
Abstract Background: AML is characterized by molecular heterogeneity; morphology and genetic alterations are important prognostic factors (Weinberg, 2009). In the large, phase 3, multicenter, randomized AZA-AML-001 study, AZA treatment (Tx) prolonged median overall survival (OS) vs CCR by ~4 months (10.4 vs 6.5 mo; p=0.1009) in older pts with newly diagnosed AML (>30% BM blasts). About 33% of patients (pts) in AZA-AML-001 had AML with morphologic dysplastic changes (AML-MDC). Aim: Determine effects of AZA vs CCR on OS, response, and safety in the subset of pts with AML-MDC in the AZA-AML-001 trial; and further analyze OS in AML-MDC pts who had been preselected to receive low-dose cytarabine (LDAC) before randomization to AZA or CCR. Methods: Eligible pts were age ≥65 years (yrs), had AML with >30% BM blasts, ECOG performance status (PS) 0-2, WBC count ≤15x109/L, and intermediate- or poor-risk cytogenetics. This analysis includes pts who, based on local assessment, had AML-MDC.Before randomization, investigators preselected the preferred Tx option for each pt from 3 CCR: intensive chemotherapy (IC; standard 7 + 3 regimen), LDAC (20mg SC BID x 10 days [d]/28d cycle), or best supportive care (BSC) only. Pts were then randomized to AZA (75mg/m2/d x 7 d/28d cycle) or CCR, and then received the preselected CCR. Median OS (Kaplan-Meier method) and percent of pts alive at 1 yr were compared between AZA vs CCR for all pts with AML-MDC, and between AZA vs LDAC specifically in pts with AML-MDC preselected to LDAC before randomization. Response was assessed by IWG AML criteria (Cheson, 2003). Transfusion independence (TI) was defined as no transfusion for 56 consecutive days for transfusion dependent (TD) pts at baseline (ie, ≥1 transfusion in 56d before randomization). Overall response was defined as complete remission (CR) + morphologic CR with incomplete blood count recovery (CRi). Adverse events (AEs) were graded by NCI-CTCAE v4. Hazard ratios (HR) and 95% confidence intervals (95%CI) were determined by unstratified Cox proportional hazards model and p values from log-rank or Fisher's exact test. Results: Of 488 pts in AZA-AML-001, 158 (32.4%) had AML-MDC and are included in these analyses. Baseline characteristics were generally balanced between Tx arms (AZA n=75, CCR n=83 [IC n=13, LDAC n=50, and BSC n=20]). Median (range) ages were 76 (65, 86) and 74 (66, 87) yrs in the AZA and CCR groups, respectively. Higher proportions of pts in the AZA arm were age ≥75 yrs (59% vs 48% of CCR) and had prior MDS (47% vs 37%). In the AZA and CCR arms, 43% and 47% of pts had poor-risk cytogenetics, and 24% and 25% had ECOG PS score of 2. Median (range) %BM blasts (central review) in the AZA and CCR arms was 67% (4, 99) and 73% (9, 100). Mediannumber of Tx cycles with AZA, IC, and LDAC were 6 (1, 28), 1 (1, 3), and 3 (1, 23). Median exposure to BSC was 79 d (8, 535). Median OS in pts with AML-MDC was prolonged 2-fold with AZA vs CCR: 12.7 mo (95%CI 7.2, 14.1) vs 6.3 mo (4.3, 9.6); HR=0.69 (0.48, 0.98), p=0.0357 (Figure). Similarly, 1-yr survival was greater with AZA: 50.7% vs 33.8% with CCR (16.9% difference [95%CI 1.5, 32.2]). Rates of CR+CRi were 26.7% with AZA vs 19.3% with CCR (Table). Most pts with AML-MDC (n=99, 63%) were preselected to receive LDAC (AZA n=49, LDAC n=50). Median OS in the preselected LDAC group with AZA vs LDAC, respectively, was 13.2 mo vs 6.3 mo, a 6.8-mo improvement with AZA (HR=0.76 [95%CI 0.49, 1.19], p=0.23). Further, 1-yr survival with AZA vs LDAC was 55% vs 31% (24% difference [95%CI 5.0, 43.0]). In the overall AML-MDC group with baseline-TD, 16/51 (31%) and 14/58 (24%) attained RBC TI in the AZA and CCR groups, and 10/26 (39%) and 12/33 (36%) attained platelet TI. Grade 3-4 anemia, neutropenia, febrile neutropenia, and thrombocytopenia rates, respectively, were: AZA 12%, 30%, 30%, 28%; IC 15%, 46%, 39%, 31%; LDAC 16%, 29%, 35%, 27%; and BSC 6%, 11%, 44%, 11%. Conclusions: AZA prolonged median OS 2-fold to >1 yr in this older, poor-risk subgroup of pts with AML-MDC. More than one-half of AZA-treated pts with AML-MDC remained alive at 1 yr. Notably, median OS in pts preselected to LDAC, but who were randomized to AZA, was more than doubled vs pts who did receive LDAC. AZA safety profile was consistent with that seen in the entire AZA-AML-001 population (Dombret, 2014). Compared with commonly used CCR, AZA was safe, effective and well- tolerated in this subset of pts with AML. These data suggest AZA may be a beneficial initial Tx as an alternative to LDAC in pts with AML-MDC. Figure 1 Figure 1. Figure 2 Figure 2. Disclosures Seymour: Celgene: Consultancy, Honoraria, Speakers Bureau. Off Label Use: Use of azacitidine in AML with blast count >30%. Döhner:Celgene: Consultancy. Wierzbowska:Celgene: Honoraria, Speakers Bureau. Selleslag:Celgene: Consultancy, Research Funding, Speakers Bureau. Cavenagh:Celgene: Honoraria. Kumar:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Schuh:Celgene: Membership on an entity's Board of Directors or advisory committees. Candoni:Celgene: Consultancy, Speakers Bureau. Récher:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Sandhu:Celgene: Honoraria. Bernal del Castillo:Celgene: Consultancy. Al-Ali:Celgene: Honoraria, Research Funding. Martinelli:Novartis: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau; Pfizer: Consultancy; ARIAD: Consultancy. Falantes:Celgene: Consultancy. Stone:Agios: Consultancy; AbbVie: Consultancy; Amgen: Consultancy; Celator: Consultancy; Celgene: Consultancy; Roche: Consultancy. Minden:Celgene: Honoraria. McIntyre:Celgene: Employment. Songer:Celgene: Employment, Equity Ownership. Lucy:Celgene: Employment, Equity Ownership. Beach:Celgene: Employment, Equity Ownership. Dombret:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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 ».