关键词: 乳腺癌, 人表皮生长因子受体2, 超声弹性成像, 超声造影, 列线图

Abstract:

Objective To evaluate the predictive value of a nomogram model developed by integrating clinical and ultrasound multiparameters for HER-2-positive breast cancer. Methods This study retrospectively enrolled 343 patients with pathologically confirmed breast cancer from three medical centers and randomly divided them into training and validation cohorts. Univariate analysis， LASSO regression， and multivariate logistic regression were conducted on the training set to identify independent prognostic factors and construct a nomogram model. Bootstrap resampling with 1000 iterations was performed to evaluate the model′s robustness. Model calibration was assessed using calibration curves and the Hosmer-Lemeshow goodness-of-fit test. Receiver operating characteristic （ROC） curves were generated to evaluate model discrimination， and the area under the curve （AUC） along with other performance metrics were calculated. Decision curve analysis was employed to assess the clinical utility of the model， and the validation cohort was used for external validation. Results Univariate， LASSO， and multivariate regression analyses demonstrated that age， TTP （time to peak）， and the presence of a filling defect sign were independent predictors of HER-2-positive breast cancer （all P < 0.05）. Based on these independent predictors， a nomogram model was constructed. Bootstrap validation with 1，000 resamples indicated that the model′s predictive performance was stable. The Hosmer-Lemeshow test confirmed satisfactory model calibration， while the calibration curve illustrated accurate prediction probabilities. The area under the curve （AUC） for the training set was 0.863 （95%CI： 0.806 ~ 0.920）， and for the validation set， it was 0.846 （95%CI： 0.764 ~ 0.929）， indicating strong discriminative and generalization capabilities. Additionally， the clinical decision curve analysis demonstrated favorable clinical utility. Conclusion A nomogram model integrating clinical and multimodal ultrasound parameters demonstrates potential utility in predicting HER-2-positive breast cancer.

Key words: breast cancer, human epidermal growth factor receptor 2, ultrasound elastography, contrast-enhanced ultrasound, nomogram