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Updated: Jun 26, 2026

Modeling Chemotherapy Resistant Leukemia In Vitro
Published on: February 9, 2016
A Nomogram Prediction Model and Scoring System for Resistance in Acute Myeloid Leukemia Patients Treated with
Qingqing Fan1, Yujiao Guo1, Xiang Hui1
1Department of Pharmacy, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.
Abstract:
To investigate the predictive factors for resistance to VEN combined with HMAs in the treatment of AML, construct a drug resistance prediction model, and visualize the model. A retrospective analysis was conducted on 74 AML patients. Multivariate logistic regression was used to identify independent predictors of primary resistance, based on which a nomogram model and a risk scoring system for drug resistance were constructed. The results showed that KIT (p = 0.012), TP53 (p = 0.010), and FAB-M5 (p = 0.059) were significantly associated with primary resistance to VEN. A nomogram prediction model incorporating FAB-M5, KIT, and TP53 was established. Based on the nomogram model, a drug resistance prediction scoring tool comprising three variables was developed, categorizing patients into high-risk (6-10 points), intermediate-risk (3-5 points), and low-risk (0-2 points) groups. Significant differences in NR rates were observed among the three risk groups (p < 0.001). KIT, TP53, and FAB-M5 are independent factors influencing VEN resistance. The constructed nomogram prediction model and scoring system may provide valuable references for predicting primary resistance to VEN.
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