Phase 3 trial of gilteritinib plus azacitidine vs azacitidine for newly diagnosed <i>FLT3</i>mut+ AML ineligible for intensive chemotherapy
Bibliographic record
Abstract
Treatment results for patients with newly diagnosed FMS-like tyrosine kinase 3 (FLT3)-mutated (FLT3mut+) acute myeloid leukemia (AML) ineligible for intensive chemotherapy are disappointing. This multicenter, open-label, phase 3 trial randomized (2:1) untreated adults with FLT3mut+ AML ineligible for intensive induction chemotherapy to receive gilteritinib (120 mg/d orally) and azacitidine (GIL + AZA) or azacitidine (AZA) alone. The primary end point was overall survival (OS). At the interim analysis (August 26, 2020), a total of 123 patients were randomized to treatment (GIL + AZA, n = 74; AZA, n = 49). Subsequent AML therapy, including FLT3 inhibitors, was received by 20.3% (GIL + AZA) and 44.9% (AZA) of patients. Median OS was 9.82 (GIL + AZA) and 8.87 (AZA) months (hazard ratio, 0.916; 95% CI, 0.529-1.585; P = .753). The study was closed based on the protocol-specified boundary for futility. Median event-free survival was 0.03 month in both arms. Event-free survival defined by using composite complete remission (CRc) was 4.53 months for GIL + AZA and 0.03 month for AZA (hazard ratio, 0.686; 95% CI, 0.433-1.087; P = .156). CRc rates were 58.1% (GIL + AZA) and 26.5% (AZA) (difference, 31.4%; 95% CI, 13.1-49.7; P < .001). Adverse event (AE) rates were similar for GIL + AZA (100%) and AZA (95.7%); grade ≥3 AEs were 95.9% and 89.4%, respectively. Common AEs with GIL + AZA included pyrexia (47.9%) and diarrhea (38.4%). Gilteritinib steady-state trough concentrations did not differ between GIL + AZA and gilteritinib. GIL + AZA resulted in significantly higher CRc rates, although similar OS compared with AZA. Results support the safety/tolerability and clinical activity of upfront therapy with GIL + AZA in older/unfit patients with FLT3mut+ AML. This trial was registered at www.clinicaltrials.gov as #NCT02752035.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".