Affiliation:
1. Department of Ultrasound, Beijing Friendship Hospital Capital Medical University Beijing China
2. School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China
3. Clinical Epidemiology and EBM Unit, Beijing Friendship Hospital Capital Medical University, Beijing Clinical Research Institute Beijing China
4. Department of Pathology, Beijing Friendship Hospital Capital Medical University Beijing China
Abstract
ObjectivesTo explore the clinical value of the nomogram based on ultrasound spectral combined with clinical pathological parameter in predicting axillary lymph node metastasis in breast cancer.MethodsWe prospectively gathered clinicopathologic and ultrasonic data from 240 patients confirmed breast cancer. The risk factors of axillary lymph node metastasis were analyzed by univariate and multivariate logistic regression, and the prediction model was established. The model calibration, predictive ability, and diagnostic efficiency in the training set and the testing set were analyzed by receiver operating characteristic curve and calibration curve analysis, respectively.ResultsUnivariate analysis showed that lymph node metastasis was related with tumor size, Ki‐67, axillary ultrasound, ultrasound spectral quantitative parameter, internal echo, and calcification (P < .05). Multivariate logistic regression analysis showed that the Ki‐67, axillary ultrasound, quantitative parameter (the mean of the mid‐band fit in tumor and posterior tumor) were independent risk factors of axillary lymph node metastasis (P < .05). The models developed using Ki‐67, axillary ultrasound, and quantitative parameters for predicting axillary lymph node metastasis demonstrated an area under the receiver operating characteristic curve of 0.83. Additionally, the prediction model exhibited outstanding predictability for axillary lymph node metastasis, as evidenced by a Harrell C‐index of 0.83 (95% confidence interval 0.73–0.93).ConclusionAxillary ultrasound combined with Ki‐67 and ultrasound spectral parameters has the potential to predict axillary lymph node metastasis in breast cancer, which is superior to axillary ultrasound alone.
Funder
National Natural Science Foundation of China