Journal of Shanghai Jiao Tong University (Medical Science) ›› 2022, Vol. 42 ›› Issue (4): 502-509.doi: 10.3969/j.issn.1674-8115.2022.04.013

• Clinical research • Previous Articles     Next Articles

Construction and evaluation of a prediction model for liver injury induced by chemotherapy for breast cancer

XIA Kunjian1(), DENG Linlin2, WANG Lin1()   

  1. 1.Department of Breast Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
    2.Department of Critical Care Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
  • Received:2022-01-07 Accepted:2022-04-10 Online:2022-04-28 Published:2022-04-28
  • Contact: WANG Lin E-mail:1395091242@qq.com;w7102l@163.com

Abstract: Objective

·To analyze the risk factors of liver injury induced by chemotherapy for breast cancer, and to construct and evaluate a prediction model of liver injury induced by chemotherapy.

Methods

·Breast cancer patients hospitalized at the Second Affiliated Hospital of Nanchang University from April 2019 to September 2021 who received anthracycline combined with cyclophosphamide sequential paclitaxel ± trastuzumab chemotherapy were enrolled in the study, and were divided into liver injury group and non-injury group. The risk factors of liver injury induced by chemotherapy were analyzed by χ2 test and binary Logistic regression, and the prediction model was established. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of the regression model, and then the predictive model was externally validated.

Results

·Two hundred and seven patients with breast cancer met the inclusion criteria in this study, and sixty-nine patients with liver injury (33.3%). Univariate analysis showed that the difference of chemotherapy regimen (χ2=44.851, P=0.000), hepatitis B virus infection (χ2=16.682, P=0.000), previous history of hypertension (χ2=13.211, P=0.004), tumor TNM staging (χ2=14.422, P=0.001), previous history of diabetes (χ2=4.839, P=0.028), low albumin level before chemotherapy (χ2=10.073, P=0.002) and elevated triacylglycerol (χ2=39.367, P=0.000) were statistically significant between the two groups. Binary Logistic regression showed that chemotherapy regimen (OR=4.734, 95%CI 1.687?13.283, P=0.003), hepatitis B virus infection (OR=4.530, 95%CI 1.806?11.366, P=0.001), tumor TNM stage Ⅲ (OR=5.304, 95%CI 1.802-15.608, P=0.002), previous history of diabetes (OR=3.041, 95%CI 1.196?7.729, P=0.019), and low albumin level before chemotherapy (OR=3.744, 95%CI 1.413?9.920, P=0.008) were independent risk factors for liver injury caused by chemotherapy. logit(P)=-3.471+1.511?X1+1.112?X2+1.320?X3+0.755?X4+0.691?X5+0.973?X6+1.258?X7+0.741?X8+1.668?X9+1.555?X10. The area under the ROC curve was 0.874, the standard error was 0.024, 95%CI 0.827?0.922, P=0.000. External validation showed that the specificity of the prediction model was 86.9%, the sensitivity was 76.9%; the positive predictive value was 71.4%, the negative predictive value was 89.8%; the accuracy was 83.9%; the Kappa value was 0.624, the standard error was 0.091, P=0.000.

Conclusion

·This Logistic regression model has high predictive performance and has certain reference value for breast doctors to predict whether patients have liver damage.

Key words: breast cancer, liver injury, predictive model, ROC curve, Kappa consistency test

CLC Number: