Clinical benefit of glasdegib plus low-dose cytarabine in patients with de novo and secondary acute myeloid leukemia: long-term analysis of a phase II randomized trial
Bibliographic record
Abstract
This analysis from the phase II BRIGHT AML 1003 trial reports the long-term efficacy and safety of glasdegib + low-dose cytarabine (LDAC) in patients with acute myeloid leukemia ineligible for intensive chemotherapy. The multicenter, open-label study randomized (2:1) patients to receive glasdegib + LDAC (de novo, n = 38; secondary acute myeloid leukemia, n = 40) or LDAC alone (de novo, n = 18; secondary acute myeloid leukemia, n = 20). At the time of analysis, 90% of patients had died, with the longest follow-up since randomization 36 months. The combination of glasdegib and LDAC conferred superior overall survival (OS) versus LDAC alone; hazard ratio (HR) 0.495; (95% confidence interval [CI] 0.325-0.752); p = 0.0004; median OS was 8.3 versus 4.3 months. Improvement in OS was consistent across cytogenetic risk groups. In a post-hoc subgroup analysis, a survival trend with glasdegib + LDAC was observed in patients with de novo acute myeloid leukemia (HR 0.720; 95% CI 0.395-1.312; p = 0.14; median OS 6.6 vs 4.3 months) and secondary acute myeloid leukemia (HR 0.287; 95% CI 0.151-0.548; p < 0.0001; median OS 9.1 vs 4.1 months). The incidence of adverse events in the glasdegib + LDAC arm decreased after 90 days' therapy: 83.7% versus 98.7% during the first 90 days. Glasdegib + LDAC versus LDAC alone continued to demonstrate superior OS in patients with acute myeloid leukemia; the clinical benefit with glasdegib + LDAC was particularly prominent in patients with secondary acute myeloid leukemia. ClinicalTrials.gov identifier: NCT01546038.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".