Predicting Axillary Lymph Node Status With a Nomogram Based on Breast Lesion Ultrasound Features: Performance in N1 Breast Cancer Patients

Frontiers in Oncology
Yanwen LuoQingli Zhu

Abstract

To develop a nomogram for predicting axillary lymph node (ALN) metastases using the breast imaging reporting and data system (BI-RADS) ultrasound lexicon. A total of 703 patients from July 2015 to January 2018 were included in this study as a primary cohort for model construction. Moreover, 109 patients including 51 pathologically confirmed N1 patients (TNM staging) and 58 non-metastatic patients were recruited as an external validation cohort from March 2018 to August 2019. Ultrasound images and clinical information of these patients were retrospectively reviewed. The ultrasonic features based on the BI-RADS lexicon were extracted by two radiologists. The features extracted from the primary cohort were used to develop a nomogram using multivariate analysis. Internal and external validations were performed to evaluate the predictive efficacy of the nomogram. The nomogram was based on two features (size, lesion boundary) and showed an area under the curve of 0.75 (95% confidence interval [CI], 0.70-0.79) in the primary cohort and 0.91 (95% CI, 0.84-0.97) in the external validation cohort; it achieved an 88% sensitivity in N1 patients. The nomogram based on BI-RADS ultrasonic features can predict breast cancer ALN status with rel...Continue Reading

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Methods Mentioned

BETA
biopsy
dissection
feature extraction

Software Mentioned

R
EmpowerStats
pROC

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