Randomized comparison of low dose cytarabine with or without glasdegib in patients with newly diagnosed acute myeloid leukemia or high-risk myelodysplastic syndrome
Bibliographic record
Abstract
Glasdegib is a Hedgehog pathway inhibitor. This phase II, randomized, open-label, multicenter study (ClinicalTrials.gov, NCT01546038) evaluated the efficacy of glasdegib plus low-dose cytarabine (LDAC) in patients with acute myeloid leukemia (AML) or high-risk myelodysplastic syndrome unsuitable for intensive chemotherapy. Glasdegib 100 mg (oral, QD) was administered continuously in 28-day cycles; LDAC 20 mg (subcutaneous, BID) was administered for 10 per 28 days. Patients (stratified by cytogenetic risk) were randomized (2:1) to receive glasdegib/LDAC or LDAC. The primary endpoint was overall survival. Eighty-eight and 44 patients were randomized to glasdegib/LDAC and LDAC, respectively. Median (80% confidence interval [CI]) overall survival was 8.8 (6.9-9.9) months with glasdegib/LDAC and 4.9 (3.5-6.0) months with LDAC (hazard ratio, 0.51; 80% CI, 0.39-0.67, P = 0.0004). Fifteen (17.0%) and 1 (2.3%) patients in the glasdegib/LDAC and LDAC arms, respectively, achieved complete remission (P < 0.05). Nonhematologic grade 3/4 all-causality adverse events included pneumonia (16.7%) and fatigue (14.3%) with glasdegib/LDAC and pneumonia (14.6%) with LDAC. Clinical efficacy was evident across patients with diverse mutational profiles. Glasdegib plus LDAC has a favorable benefit-risk profile and may be a promising option for AML patients unsuitable for intensive chemotherapy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.002 |
| 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".