Randomized, phase 2 trial of low-dose cytarabine with or without volasertib in AML patients not suitable for induction therapy
Bibliographic record
Abstract
Treatment outcomes for older patients with acute myeloid leukemia (AML) have remained dismal. This randomized, phase 2 trial in AML patients not considered suitable for intensive induction therapy compared low-dose cytarabine (LDAC) with or without volasertib, a highly potent and selective inhibitor of polo-like kinases. Eighty-seven patients (median age 75 years) received LDAC 20 mg twice daily subcutaneously days 1-10 or LDAC + volasertib 350 mg IV days 1 + 15 every 4 weeks. Response rate (complete remission and complete remission with incomplete blood count recovery) was higher for LDAC + volasertib vs LDAC (31.0% vs 13.3%; odds ratio, 2.91; P = .052). Responses in the LDAC + volasertib arm were observed across all genetic groups, including 5 of 14 patients with adverse cytogenetics. Median event-free survival was significantly prolonged by LDAC + volasertib compared with LDAC (5.6 vs 2.3 months; hazard ratio, 0.57; 95% confidence interval, 0.35-0.92; P = .021); median overall survival was 8.0 vs 5.2 months, respectively (hazard ratio, 0.63; 95% confidence interval, 0.40-1.00; P = .047). LDAC + volasertib led to an increased frequency of adverse events that was most pronounced for neutropenic fever/infections and gastrointestinal events; there was no increase in the death rate at days 60 + 90. This study was registered at www.clinicaltrials.gov as #NCT00804856.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".