Efficacy and safety of venetoclax plus azacitidine based regimens in the treatment of relapsed or refractory acute myeloid leukemia: a systematic review and meta-analysis
Bibliographic record
Abstract
This meta-analysis aimed to evaluate the efficacy and safety of venetoclax plus azacitidine (VEN + AZA) regimens in patients with relapsed or refractory acute myeloid leukemia (R/R AML) and to explore the effects of different combination strategies, including chemotherapy and targeted agents, on clinical outcomes. A systematic search of PubMed, Web of Science, Embase, and Cochrane Library databases was performed up to February 2025. Studies that reported complete remission or complete remission with incomplete hematologic recovery (CR/CRi) were included. Study quality was assessed using the Newcastle-Ottawa Scale (NOS) for Non-Randomized Controlled Trials (NRCTs). Pooled estimates were calculated using random-effects models, and subgroup analyses were performed. The CR/CRi rate for VEN + AZA-based regimens was 43% (95% CI: 33-53%), with substantial heterogeneity (I²=89.20%). Subgroup analysis indicated higher CR/CRi rates for VEN + AZA combined with chemotherapy (68%, 95% CI: 62-73%) compared to VEN + AZA alone (38%, 95% CI: 28-47%) or VEN + AZA with targeted agents (28%, 95% CI: 18-40%). The most common grade ≥ 3 adverse events were neutropenia (89%) and thrombocytopenia (82%). VEN + AZA combined with chemotherapy significantly improved CR/CRi rates in R/R AML compared to VEN + AZA alone or with targeted agents.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.043 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".