Effect of enasidenib (ENA) plus azacitidine (AZA) on complete remission and overall response versus AZA monotherapy in mutant<i>-IDH2</i> (<i>mIDH2</i>) newly diagnosed acute myeloid leukemia (ND-AML).
Bibliographic record
Abstract
7501 Background: ENA and AZA each induce overall response rates (ORR) of ~30% and complete remission (CR) rates of ~20% in ND-AML. In vitro, combining ENA + AZA enhances cell differentiation. We report results of the phase II portion of an open-label, randomized phase I/II study of ENA + AZA (“E+A”) vs. AZA monotherapy (“A”) in patients (pts) with m IDH2 ND-AML (NCT02677922). Methods: Pts age ≥ 18 years ineligible for intensive chemotherapy, with ECOG PS ≤ 2 and intermediate- or poor-risk cytogenetics, were randomized 2:1 to E+A or A in 28-day (d) cycles. All pts received SC AZA 75 mg/m 2 /d x 7 d/cycle; pts randomized to E+A also received ENA 100 mg QD. The primary endpoint was ORR (CR, CR with incomplete recovery, partial remission, morphologic leukemia-free state). Other endpoints include duration of response (DOR), overall and event-free survival (OS, EFS), safety, and m IDH2 VAF. Results: 101 pts received E+A (n = 68) or A (n = 33). Median age was 75 years (57–85); most pts (83%) had intermediate-risk cytogenetics. 21 pts in the E+A arm and 1 in the A arm were ongoing at data cutoff (Aug 2019). Most common reason for discontinuation was disease progression (E+A 31%, A 52%). Median number Tx cycles was 10 (1–26) in the E+A arm and 6 (1–28) in the A arm. 7 pts (21%) in the A arm received subsequent Tx with ENA. ORR, CR rate and DOR were significantly improved with E+A vs. A (Table). Median OS was 22 mo in both arms (HR 0.99 [95%CI 0.52, 1.87]; P = 0.97). Median EFS was 17.2 and 10.8 mo in the E+A and A arms, respectively (HR 0.59 [95%CI 0.30, 1.17]; P = 0.13). Maximal m IDH2 VAF change from BL was –83.4% with E+A vs. –17.7% with A ( P < 0.01). No baseline co-mutation predicted primary resistance. Common Tx-related grade 3–4 AEs in the E+A arm were thrombocytopenia (37%), neutropenia (35%), anemia (19%), and febrile neutropenia (15%); these occurred in 19%, 22%, 22%, and 16% in the A arm. Grade 3–4 infections occurred in 18% of E+A pts and 31% of A pts. IDH differentiation syndrome occurred in 12 pts (18%) in the E+A arm. 5 E+A pts (7%) and 1 A pt (3%) died in the first 60 d. Conclusions: Combining ENA + AZA resulted in significantly improved response rates and durations, and was generally well-tolerated in older patients with m IDH2 ND-AML. The impact of subsequent Tx on OS/EFS and new translational data will be presented at the meeting. Clinical trial information: NCT02677922 . [Table: see text]
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".