Cancer chemotherapy and pharmacology · 2025
Risk factors and prediction models for cardiotoxicity induced by anthracyclines in malignant chemotherapy.
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Zhang Pengxiang, Zhang Yan, Xue Zheng, Liu Dongchao, Li Dongliang, Duan Bing, Zhao Meina, Yin Liang, Gao Hongjie, Gao Bulang, Mi Jie
Аннотация
PURPOSE: To investigate risk factors for cancer therapy-related cardiac dysfunction (CTRCD) in patients receiving anthracycline-based chemotherapy and develop a predictive model for assessing the risk of CTRCD. MATERIALS AND METHODS: Patients with breast cancer or lymphoma who underwent chemotherapy were retrospectively enrolled. Independent risk factors were identified for CTRCD, and a clinical prediction model (nomogram) was constructed and evaluated. RESULTS: 324 patients were randomly divided into the training and validation cohorts, and patients in the training cohort were further divided into the CTRCD positive (n = 48) and negative cohort (n = 222). Body mass index (BMI) ≥ 25, brain natriuretic peptide (BNP) acuity 52 pg/ml, pathologic stage, low density lipoprotein (LDL) or greater tendency for 3.37 / L, combined HER-2 class drugs, and cumulative dose of anthracycline of 550 mg /m2 were independent risk factors for CTRCD. The C-index of the CTRCD prediction map was 0.872 (95% confidence interval or CI: 0.821–0.923) in the training cohort, similar to that of 0.886 (95% CI: 0.799–0.974) in the validation cohort. The cut-off value of the receiver operating characteristics (ROC) curve analysis in the training cohort was 0.164. Good agreement was shown in the predicted data of the training group (P = 0.837) and the verification group (P = 0.700). The observed probability predicting CTRCD was close to the actual probability. The decision curve analysis (DCA) showed that the constructed nomogram had a high clinical application prospect. CONCLUSION: BMI ≥ 25, history of diabetes, BNP ≥ 52 pg/ml, LDL ≥ 3.37 mmol/L, pathological stage, and cumulative anthracycline dose ≥ 550 mg/m² were independent risk factors for CTRCD. The nomogram model demonstrates excellent predictive accuracy, with a C-index of 0.872 in the training cohort and 0.886 in the validation cohort, offering a reliable tool for identifying high-risk for CTRCD.