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December 8, 2025BloodOpen Access

Real-world efficacy and prognostic modeling of venetoclax-enhanced intensive chemotherapy in fit AML

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Authors

XHXiaobing HuangArmy Medical University

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Overview

Retrospective analysis shows venetoclax enhances treatment efficacy in fit AML, suggesting improvement in prognostic models using machine learning.

Key Points

  • The study aims to evaluate the efficacy and safety of venetoclax with intensive chemotherapy in fit AML patients and develop prognostic prediction models.
  • Retrospective analysis of 158 newly diagnosed fit AML patients.
  • Comparison of four chemotherapy regimens: DAV, IAV, HAV, and MAV.
  • Use of seven machine learning algorithms to build prognostic models.
  • Overall composite complete remission (CRc) rate was 77.2%.
  • Adverse risk patients had a significantly lower CRc than intermediate-risk (61.7% vs 83.8%, P=0.010).
  • XGBoost and Random Forest showed optimal performance for prognostic modeling.

Cite This Study

Xiaobing Huang (2025) studied this question.

synapsesocial.com/papers/69362f3a4fa91c937236d3abhttps://doi.org/10.1182/blood-2025-6985
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Retrospective evaluation of venetoclax-based regimen in newly diagnosed and relapsed/refractory acute myeloid leukemia: Efficacy determinants, survival outcomes, and model validation2026
  2. 2Predictive Models for Long Term Survival of AML Patients Treated with Venetoclax and Azacitidine or 7+3 Based on Post Treatment Events and Responses: Retrospective Cohort Study2024 · 9 citations
  3. 3Genetic risk stratification in adults with AML receiving venetoclax-based intensive therapy: A real-world study2025
  4. 4Risk stratification of low-dose cytarabine and venetoclax in patients with AML ineligible for intensive chemotherapy2025
  5. 5AI-derived prediction of response and relapse to venetoclax plus hypomethylating agent based therapy in Acute Myeloid Leukemia2025