Prognostic Impact of <i>NPM1</i> and <i>FLT3</i> Mutations at Diagnosis and Presence of Measurable Residual Disease (MRD) after Intensive Chemotherapy (IC) for Patients with Acute Myeloid Leukemia (AML) in Remission: Outcomes from the QUAZAR AML-001 Trial of Oral Azacitidine (Oral-AZA) Maintenance
Bibliographic record
Abstract
Abstract BACKGROUND: Current guidelines for AML ascribe disease-risk partly based on NPM1 and FLT3 mutational status. NPM1 mutations (mut) occur in 25%-30% of patients (pts) with AML and are associated with favorable prognosis in the absence of co-occurring FLT3-ITD. FLT3-ITD alterations are observed in ~15-30% of AML pts and confer poor prognosis, whereas the prognostic implication of FLT3-TKD point mutations (~7% of pts) is less clear. Post-IC, absence of MRD is associated with favorable relapse-free and overall survival (RFS/OS). In the randomized, phase 3 QUAZAR AML-001 trial, Oral-AZA (CC-486) significantly prolonged OS and RFS vs placebo (PBO) in older pts with AML in first remission after IC (Wei, NEJM 2020). It is of high interest to understand the effects of Oral-AZA in pts with NPM1 and/or FLT3 mutations, and whether their outcomes are influenced by post-IC MRD status. OBJECTIVE: Evaluate survival outcomes with Oral-AZA vs PBO in pts with NPM1mut ± FLT3mut at AML diagnosis (Dx), and OS by baseline (BL) MRD status (+/-) in pts with NPM1/FLT3 mutations. METHODS: In QUAZAR AML-001, pts aged ≥55 years with AML and NCCN intermediate or poor-risk cytogenetics at Dx were randomized 1:1 to receive Oral-AZA 300 mg or PBO QD within 4 mo after attaining first CR/CRi with IC (induction ± consolidation). NPM1 and FLT3 statuses (mut or wild-type [wt]) at AML Dx (before IC) were collected from pt diagnostic case report forms. MRD analyses were conducted by MFC (≥0.1% MRD+ cutoff) in bone marrow aspirate samples collected at screening (post-IC; ie, BL). OS and RFS were estimated from the time of randomization using Kaplan-Meier methods. Multivariate (MV) Cox regression analyses of the prognostic effects on OS/RFS were performed, with NPM1 and FLT3 mutational status and cytogenetic risk at Dx; post-IC MRD status (+/-) at BL, and randomized Tx (Oral AZA vs PBO) as variables. RESULTS: Of 472 pts enrolled , 469 (99.4%) had mutational data available at Dx, and the MRD-evaluable cohort comprised 463 pts (98.1%). In all, 137 pts (29%; Oral-AZA n = 66, PBO n = 71) had NPM1mut at AML Dx, and NPM1mut was significantly correlated with MRD- status at BL (post-IC)(P = 0.0178). Among pts with NPM1mut, OS was significantly improved in pts receiving Oral-AZA vs PBO, whether pts were MRD- (median 48.6 vs 26.2 mo, respectively) or MRD+ (median 39.4 vs 10.3 mo) at BL (both P < 0.0001) (Figure). While median OS for NPM1mut pts in the Oral-AZA arm was nominally improved for MRD- pts vs. those MRD+ (48.6 vs. 39.4 mo, respectively), median OS for NPM1mut pts in the PBO arm was substantially influenced by post-IC MRD status (26.2 vs 10.3 mo for MRD- and MRD+ pts, respectively) (Figure). Similarly, median RFS for pts with NPM1mut/MRD- in the Oral-AZA and PBO arms was 24.9 vs 9.9 mo, respectively, and for pts with NPM1mut/MRD+ was 19.4 vs 4.6 mo. In all, 66 pts (14.1%) had FLT3-ITD (n = 46) and/or FLT3-TKD mut (n = 24) at AML Dx; NPM1 and FLT3-ITD status was NPM1mut + FLT3-ITD - in 107 pts, NPM1mut + FLT3-ITD + in 30 pts, and NPM1wt + FLT3-ITD + in 16 pts. In the Oral-AZA arm, median OS in pts with FLT3mut was not meaningfully different from that in pts with FLT3wt (28.2 and 24.7 mo, respectively), but FLT3mut conferred a negative prognosis in the PBO arm (median OS 9.7 mo, vs 15.2 mo for FLT3wt pts). Risk of death was reduced 46% with Oral-AZA vs PBO in pts with FLT3mut (HR 0.54 [95%CI 0.25, 1.14]). When considering MRD status, median OS in FLT3mut/MRD- pts was 28.2 vs. 15.9 mo in the Oral-AZA (n = 14) and PBO (n = 17) arms, respectively, and was 24.0 vs 8.0 mo in FLT3mut/MRD+ pts (Oral-AZA, n = 16; PBO, n = 18). In MV analyses, Oral-AZA significantly improved OS vs PBO when adjusted for other variables (P = 0.035); NPM1 status (P = 0.001), FLT3status (P = 0.035), and cytogenetic risk at Dx (P < 0.001) were each also significantly predictive of OS, as was post-IC MRD status (P < 0.001). All except FLT3 status (P = 0.737) were significantly predictive of RFS. CONCLUSIONS: Oral-AZA prolonged OS and RFS vs PBO in pts with NPM1mut, with improvements beyond the prognostic benefit conferred by MRD-, suggesting that pts with NPM1mut and MRD- can attain substantial OS benefit with Oral-AZA maintenance. An OS benefit was also observed with Oral-AZA vs PBO in pts in FLT3mut at Dx, but outcomes may be confounded by co-occurring NPM1mut, so further investigation is needed. MV analyses confirmed the independent prognostic influence of Oral-AZA, NPM1 and FLT3 mutations at Dx, cytogenetic risk at Dx, and post-IC MRD status on OS. Figure 1 Figure 1. Disclosures Döhner: Janssen: Honoraria; Helsinn: Honoraria; Gilead: Honoraria; GEMoaB: Honoraria; Celgene: Honoraria, Research Funding; Bristol Myers Squibb: Honoraria, Research Funding; Berlin-Chemie: Honoraria; AstraZeneca: Honoraria; Astex Pharmaceuticals: Honoraria; Astellas: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Jazz Pharmaceuticals: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; Oxford Biomedica: Honoraria; Pfizer: Research Funding; Roche: Honoraria. Wei: Astellas: Honoraria; Novartis, Celgene, AbbVie, Servier, AstraZeneca, and Amgen: Research Funding; Novartis, Janssen, Amgen, Roche, Pfizer, Abbvie, Servier, BMS, Macrogenics, Agios, Gilead: Membership on an entity's Board of Directors or advisory committees. Roboz: Glaxo SmithKline: Consultancy; Helsinn: Consultancy; AbbVie: Consultancy; Jasper Therapeutics: Consultancy; Bayer: Consultancy; Novartis: Consultancy; Actinium: Consultancy; Agios: Consultancy; Blueprint Medicines: Consultancy; Astellas: Consultancy; AstraZeneca: Consultancy; Jazz: Consultancy; Daiichi Sankyo: Consultancy; Astex: Consultancy; Mesoblast: Consultancy; Amgen: Consultancy; MEI Pharma - IDMC Chair: Consultancy; Bristol Myers Squibb: Consultancy; Janssen: Consultancy; Otsuka: Consultancy; Celgene: Consultancy; Janssen: Research Funding; Pfizer: Consultancy; Roche/Genentech: Consultancy. Montesinos: Agios: Consultancy; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sanofi: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Tolero Pharmaceutical: Consultancy; Incyte: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Forma Therapeutics: Consultancy; Glycomimetics: Consultancy; Teva: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Astellas Pharma, Inc.: Consultancy, Honoraria, Other: Advisory board, Research Funding, Speakers Bureau; Stemline/Menarini: Consultancy. Thol: Abbvie: Honoraria; Astellas: Honoraria; BMS/Celgene: Honoraria, Research Funding; Jazz: Honoraria; Novartis: Honoraria; Pfizer: Honoraria. Ravandi: AstraZeneca: Honoraria; AbbVie: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Jazz: Honoraria, Research Funding; Xencor: Honoraria, Research Funding; Syros Pharmaceuticals: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Honoraria, Research Funding; Novartis: Honoraria; Astex: Honoraria, Research Funding; Prelude: Research Funding; Taiho: Honoraria, Research Funding. Dombret: Amgen: Honoraria, Research Funding; Incyte: Honoraria, Research Funding; Jazz Pharmaceuticals: Honoraria, Research Funding; Novartis: Research Funding; Pfizer: Honoraria, Research Funding; Servier: Research Funding; Abbvie: Honoraria; BMS-Celgene: Honoraria; Daiichi Sankyo: Honoraria. Sandhu: Celgene: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Amgen: Consultancy; Bioverativ: Consultancy; Pfizer: Consultancy; Sanofi: Consultancy; Gilead: Consultancy. Skikne: Bristol Myers Squibb: Current Employment. See: Bristol Myers Squibb: Current Employment. Ugidos: Bristol Myers Squibb: Current Employment. Risueño: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties. Chan: Bristol Myers Squibb: Current Employment. Thakurta: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties. Beach: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Lopes de Menezes: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".