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Record W4410493962 · doi:10.1186/s12885-025-14311-9

Venetoclax and hypomethylating agents versus induction chemotherapy for newly diagnosed acute myeloid leukemia patients: a systematic review and meta-analysis

2025· review· en· W4410493962 on OpenAlexaboutno aff
Yun Liu, Ying Zhang, Lijuan Wang, Fang Xie, Chengtao Zhang, Peimin Mao, Jinsong Yan

Bibliographic record

VenueBMC Cancer · 2025
Typereview
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVenetoclaxMyeloid leukemiaInduction chemotherapySurgical oncologyMeta-analysisHypomethylating agentOncologyInternal medicineChemotherapyLeukemia

Abstract

fetched live from OpenAlex

BACKGROUND: Venetoclax with hypomethylating agents (VEN-HMAs) has shown inconsistent efficacy versus induction chemotherapy (IC) in newly diagnosed AML (ND-AML). Whether or not VEN-HMAs are of clinical benefit remains uncertain. We conducted this meta-analysis to evaluate the clinical benefit of VEN-HMAs versus IC in various subtypes of ND-AML. METHODS: We searched PubMed, Embase, Cochrane Library, and Web of Science databases up to 17 June 2024. The quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). Data were extracted to perform meta-analysis or descriptive analysis. The random-effects model was used to calculate the effect sizes and 95% confidence interval (CI). Relative risk (RR) was used to estimate complete response (CR), CR/ complete response with incomplete blood count recovery (CRi), overall response rate (ORR), and 30-day mortality. Hazard ratio (HR) was used to evaluate overall survival (OS) data. RESULTS: Fifteen retrospective cohort studies with 3809 participants were identified. Compared to the IC group, the pooled RR estimates for VEN-HMAs were 1.05 (95% CI 0.88-1.26, P = 0.591) for CR, 1.09 (95% CI 0.96-1.23, P = 0.195) for CR/ CRi, 0.84 (95% CI 0.60-1.18, P = 0.318) for ORR, and 0.86 (95% CI 0.50-1.49; P = 0.596) for 30-day mortality. VEN-HMAs prolonged the OS advantage in the ND-AML population (HR = 0.80, 95% CI 0.66-0.97, P = 0.025), and was demonstrated in patients with nucleophosmin 1 (NPM1) mutation (HR = 0.64, 95% CI 0.44-0.92, P = 0.017). In AML patients with RUNX1::RUNX1T1 cytogenetic abnormalities, the pooled ORR was lower in the VEN-HMAs group (RR = 0.44, 95% CI 0.28-0.69, P < 0.001), but OS was of no significantly different (HR = 1.30, 95% CI 0.52-3.26,P = 0.58). However, only 2 studies were available and the results should be taken with caution. OS benefit was similar in other subgroup analyses based on cytogenetic risk, age, and AML type (de novo, secondary, treatment-related or prior therapy for myeloid disease cohort). CONCLUSION: Compared with the IC group, VEN-HMAs improved OS in ND-AML, especially in the NPM1 mutation subgroup (HR = 0.64), ensured the efficacy of CR, CR/CRi and ORR, without increasing 30-day mortality, necessitating further head-to-head randomized controlled trials (RCTs). TRIAL REGISTRATION: This trial was registered with PROSPERO ( www.crd.york.ac.uk/prospero/ ) on 13 July 2024, the registration number is CRD42024560585.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.034
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.116
GPT teacher head0.415
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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