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    CHEN Ziqin, LIU Zhengyang, LI Weiqi, YAN Hao, ZHANG Longzhen. Influencing factor analysis and prediction model construction for anthracycline-related cardiotoxicity in breast cancer patients[J]. Journal of Xuzhou Medical University, 2024, 44(6): 391-397. DOI: 10.3969/j.issn.2096-3882.2024.06.001
    Citation: CHEN Ziqin, LIU Zhengyang, LI Weiqi, YAN Hao, ZHANG Longzhen. Influencing factor analysis and prediction model construction for anthracycline-related cardiotoxicity in breast cancer patients[J]. Journal of Xuzhou Medical University, 2024, 44(6): 391-397. DOI: 10.3969/j.issn.2096-3882.2024.06.001

    Influencing factor analysis and prediction model construction for anthracycline-related cardiotoxicity in breast cancer patients

    • Objective To investigate the influencing factors of anthracycline-induced cardiotoxicity (ACT) in breast cancer patients, and to construct a nomogram prediction model, in order to provide evidence for the prediction and diagnosis of related patients. Methods A total of 315 breast cancer patients receiving anthracycline chemotherapy in the Affiliated Hospital of Xuzhou Medical University from January 2018 to January 2023 were selected and their clinical data were collected for retrospective analysis. According to the presence of ACT, they were divided into two groups: an ACT group (n=97) and a non-ACT group (n=218). Multivariate logistic regression analysis was conducted to analyze the influencing factors for the occurrence of ACT in breast cancer patients, and a nomogram prediction model was constructed. Results The two groups were compared for age,body mass index (BMI),hypertension history, hyperlipidemia history, myocardiac enzymes, electrocardiogram, diabetes mellitus history, the co-administration of cardioprotective agent dexrazoxane, and the cumulative dose of anthracyclines,with statistical differences (P<0.05). Multivariate logistic regression analysis indicated that age, BMI, dexrazoxane co-administration, electrocardiograms and myocardiac enzymes were the influencing factors for the occurrence of ACT. Based on the above factors, the nomogram prediction model was constructed. The model validation results showed that the area under of the receiver operating characteristic (ROC) curve was 0.862 (95% CI: 0.820-0.904), with a sensitivity of 0.825, and a specificity of 0.725, which indicated that the model had good discriminatory ability. The Hosmer-Lemeshow goodness-of-fit test showed that χ2=4.814, P=0.683, which indicated that the data of the present study fit well with the real data. Decision curve analysis demonstrated that the model had good clinical benefits. Conclusions Age≥55 years,obesity (BMI≥24 kg/m2),abnormal eletrocardiograms and myocardiac enzymes during chemotherapy are risk factors for the development of ACT in breast cancer patients. Failure to dexrazoxane co-administration is the protective factor for the development of ACT. The constructed nomogram prediction model has good differentiation and accuracy.
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