The study of correlation between nomogram prediction of uric acid and different chemotherapy regimens in breast cancer patients

Abstract

Background: High levels of serum uric acid (SUA)are associated with a poor survival rate of breast cancer.Meanwhile, a sharp increase in SUA after chemotherapy may lead to tumor lysis syndrome (TLS). We created and validated a nomogram to help doctors better manage the patient's SUA level ahead of time in this study. Methods: From July 2012 to June 2021, 206 patients with breast cancer undergoing chemotherapy participated in the study. They are randomly divided into training set (n=137) and validation set (n=69). Univariate and multivariate logistic regression analysis was used to screen the independent predictors of the risk of elevated uric acid in the whole training set data. The receiver operating characteristic (ROC) curve and decision curve assessed the accuracy and clinical application value of nomogram. Results: We confirmed that body mass index (BMI), age, menopause, EC-T chemotherapy (Epirubicin-Cyclophosphamide followed by Paclitaxel) and THP + C-T (Pirarubicin-Cyclophosphamide followed by Paclitaxel) are independent risk factors for high SUA. We established a nomogram for high SUA risk prediction to help clinicians make individualized choice of chemotherapy regimen. In the training cohort, the area under the ROC curve (AUC) showed statistical accuracy (AUC =0.796). Decision curve analysis proved the clinical value of the nomogram. Conclusions: This nomogram can be used to calculate the specific likelihood of high SUA in patients with breast cancer undergoing chemotherapy with different chemotherapy options.