Comprehensive evaluation of the diagnostic value of contrast-enhanced sonography for breast cancer by ROC curve and logistic regression

Objective To explore the diagnostic value of contrast-enhanced sonography for breast cancer by receiver operating characteristic curve (ROC curve) and a model of logistic regression. Methods Contrast-enhanced sonography was performed preoperatively in 92 women with breast mass. After analyzing the sonographic findings with logistic stepwise regression, we screened multiple diagnostic parameters for breast cancer and established a mathematical model for diagnosis. Then we assessed the diagnostic efficacy of the model and calculated the diagnostic cut-off points for breast cancer using the ROC curve. Results The area under ROC curve (AUC) of the rising slope combined with the morphological characteristics of blood flow was greater than that of either parameter alone (P 0.05). According to the regression equation P = 1 / [1+e-(-3.637+0.856X+3.153A1+3.572A2)], the cut-off point, sensitivity, specificity, and accuracy of the combined parameters for diagnosing breast cancer were 0.659, 95.8%, 84.2%, and 91.3%, respectively. Conclusion The model of logistic regression is helpful to improve the diagnostic efficacy of contrast-enhanced sonography for breast cancer.