Phase II Study of Venetoclax Added to Cladribine (CLAD) and Low Dose AraC (LDAC) Alternating with 5-Azacytidine (AZA) in Older and Unfit Patients with Newly Diagnosed Acute Myeloid Leukemia (AML)
Notice bibliographique
Résumé
Abstract Background The combination of venetoclax and 5-azacytidine (5-AZA) for older and unfit patients with newly diagnosed AML has led to significant improvements in remission rates and survival compared to 5-AZA alone. We previously reported encouraging results with a low-intensity backbone of CLAD/LDAC alternating with a hypomethylating agent (HMA) for older patients with AML observing better outcomes than historical experience with HMA alone. We hypothesized that the addition of venetoclax to the CLAD/LDAC alternating with HMA backbone may further improve outcomes for an expanded cohort of older patients with newly diagnosed AML. Methods This is a phase II study investigating the combination of venetoclax with CLAD/LDAC alternating with AZA in older (age ≥ 60y) or unfit patients with newly diagnosed AML (excluding APL, CBF). The primary objective was composite complete response rate (CRc; CR+CRi); secondary endpoints were overall survival (OS), disease-free survival (DFS), overall response rate (ORR), and toxicity. Induction was cladribine 5 mg/m 2 IV over 30 minutes on D1-5 and araC 20mg SQ BID on D1-10. Consolidation/maintenance consisted of 2 cycles of cladribine 5 mg/m 2 IV on D1-3 and araC 20 mg SQ BID on D1-10 alternating with 2 cycles of AZA 75 mg/m 2 on D1-7, for up to 18 cycles. Venetoclax 400 mg was added on days 1-21 of each cycle with dose adjustments for concomitant CYP3A inhibitors. One cycle was 4 weeks and up to 2 cycles of induction were allowed. Results A total of 60 patients were treated on study with a median age was 68 years (IQR 64 - 73, range: 57 - 84); 22 (37%) patients were ≥ 70 yrs and 1 pt < 60 yrs who was unfit for intensive chemotherapy was enrolled. 14 (23%) patients had secondary AML (sAML). 36 (60%) had diploid cytogenetics with 12 (20%) patients having adverse cytogenetics at enrollment. By European Leukemia Network (ELN) risk, 23%, 33%, and 43% were favorable, intermediate, and adverse risk, respectively. The most commonly mutated genes were NPM1 in 21 patients (33%), DNMT3A in 20 (32%), TET2 in 18 (30%), SRSF2 in 15 (25%), NRAS in 12 (20%), IDH2 in 11 (18%), RUNX1 in 11 (18%), and ASXL1 in 9 (15%). TP53 was mutated in 4 (7%) patients. Baseline characteristics are summarized in table 1. Among 60 evaluable patients the CRc rate was 93%. Best response was CR in 48 (80%), CRi in 8 (13%), no response in 3 (5%), and death in 1 (2%) patient. Responses are summarized in Figure A. In responding patients with a bone marrow sample evaluable for assessment of measurable residual disease (MRD), 43/51 (84%) were negative for MRD at response assessment. Among patients with sAML, with adverse karyotype, or ELN adverse risk the CR/CRi rate was 86% (64%/21%), 83% (58%/25%), and 96% (81%/15%) respectively. 19 (34%) responders received a subsequent allogeneic stem cell transplantation. Early mortality was low with one patient (2%) dying within 4 weeks and four patients (7%) dying with in 8 weeks. Responses are summarized in table 2. The most frequent grade 3/4 non-heme adverse events were febrile neutropenia (n=10), pneumonia (n=5), atrial fibrillation (n=2), and allergic reaction (n=2). One patient developed grade 4 tumor lysis syndrome. With a median follow up of 20.4 months, the median duration of response (DOR) is not reached (95% CI: 18 - NE months). Estimated 12- and 24-month DOR are 69.2% (95% CI: 57.5 - 83.1%) and 60.5% (95% CI: 47.7 - 76.8%), respectively. Median OS is not yet reached (95% CI: 21 - NE months). Estimated 12- and 24-month OS are 71.5% (95% CI: 60.5 - 84.5%) and 60.4% (95% CI: 47.7 - 76.6%), respectively (figure B). The estimated 12-month OS for patients aged <70 years and ≥70 years was 75% and 73%, respectively. Median DFS is not yet reached (95% CI: 18.0 - NE months). Estimated 12- and 24-month DFS are 69.2% (95% CI: 57.5 - 83.1%) and 60.5% (95% CI: 47.7 - 76.6%), respectively (figure C). Conclusion CLAD/LDAC plus venetoclax alternating with AZA plus venetoclax is an effective, lower-intensity regimen that is well tolerated among older patients (≥ 60 years) with newly diagnosed AML, producing high response rates with durable MRD negative remissions. The rates of overall and disease-free survival are encouraging in this cohort of older AML patients with comparable efficacy in patients ≥70 as in patients <70 years old. Further study of this non-anthracycline containing backbone in younger patients unfit for intensive chemotherapy, as well as comparisons to standard frontline therapies are warranted. Figure 1 Figure 1. Disclosures Kantarjian: AbbVie: Honoraria, Research Funding; Taiho Pharmaceutical Canada: Honoraria; Ascentage: Research Funding; BMS: Research Funding; Aptitude Health: Honoraria; Daiichi-Sankyo: Research Funding; Astellas Health: Honoraria; Pfizer: Honoraria, Research Funding; Immunogen: Research Funding; Novartis: Honoraria, Research Funding; Jazz: Research Funding; Amgen: Honoraria, Research Funding; Ipsen Pharmaceuticals: Honoraria; KAHR Medical Ltd: Honoraria; Astra Zeneca: Honoraria; Precision Biosciences: Honoraria; NOVA Research: Honoraria. Borthakur: Ryvu: Research Funding; ArgenX: Membership on an entity's Board of Directors or advisory committees; University of Texas MD Anderson Cancer Center: Current Employment; Astex: Research Funding; Protagonist: Consultancy; Takeda: Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees. Pemmaraju: Affymetrix: Consultancy, Research Funding; Dan's House of Hope: Membership on an entity's Board of Directors or advisory committees; Blueprint Medicines: Consultancy; ASH Communications Committee: Membership on an entity's Board of Directors or advisory committees; DAVA Oncology: Consultancy; Stemline Therapeutics, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Sager Strong Foundation: Other; LFB Biotechnologies: Consultancy; Daiichi Sankyo, Inc.: Other, Research Funding; Springer Science + Business Media: Other; Aptitude Health: Consultancy; Protagonist Therapeutics, Inc.: Consultancy; Incyte: Consultancy; Novartis Pharmaceuticals: Consultancy, Other: Research Support, Research Funding; CareDx, Inc.: Consultancy; Clearview Healthcare Partners: Consultancy; HemOnc Times/Oncology Times: Membership on an entity's Board of Directors or advisory committees; MustangBio: Consultancy, Other; Plexxicon: Other, Research Funding; ASCO Leukemia Advisory Panel: Membership on an entity's Board of Directors or advisory committees; Samus: Other, Research Funding; Bristol-Myers Squibb Co.: Consultancy; Cellectis S.A. ADR: Other, Research Funding; Roche Diagnostics: Consultancy; Abbvie Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Celgene Corporation: Consultancy; ImmunoGen, Inc: Consultancy; Pacylex Pharmaceuticals: Consultancy. DiNardo: Forma: Honoraria, Research Funding; Foghorn: Honoraria, Research Funding; AbbVie: Consultancy, Research Funding; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria; Takeda: Honoraria; Notable Labs: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Research Funding; Agios/Servier: Consultancy, Honoraria, Research Funding; ImmuneOnc: Honoraria, Research Funding; Celgene, a Bristol Myers Squibb company: Honoraria, Research Funding. Sasaki: Novartis: Consultancy, Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees. Daver: Bristol Myers Squibb: Consultancy, Research Funding; Novimmune: Research Funding; Glycomimetics: Research Funding; ImmunoGen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Trovagene: Consultancy, Research Funding; Gilead Sciences, Inc.: Consultancy, Research Funding; Hanmi: Research Funding; Abbvie: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Trillium: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Astellas: Consultancy, Research Funding; Sevier: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; FATE Therapeutics: Research Funding; Novartis: Consultancy; Jazz Pharmaceuticals: Consultancy, Other: Data Monitoring Committee member; Dava Oncology (Arog): Consultancy; Celgene: Consultancy; Syndax: Consultancy; Shattuck Labs: Consultancy; Agios: Consultancy; Kite Pharmaceuticals: Consultancy; SOBI: Consultancy; STAR Therapeutics: Consultancy; Karyopharm: Research Funding; Newave: Research Funding. Issa: Syndax Pharmaceuticals: Research Funding; Novartis: Consultancy, Research Funding; Kura Oncology: Consultancy, Research Funding. Short: Novartis: Honoraria; NGMBio: Consultancy; Takeda Oncology: Consultancy, Research Funding; Jazz Pharmaceuticals: Consultancy; AstraZeneca: Consultancy; Astellas: Research Funding; Amgen: Consultancy, Honoraria. Jain: Incyte: Research Funding; Genentech: Honoraria, Research Funding; Adaptive Biotechnologies: Honoraria, Research Funding; Cellectis: Honoraria, Research Funding; ADC Therapeutics: Honoraria, Research Funding; Pfizer
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 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,003 |
| 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 ».