Correlations of ultrasound features and immunohistochemical indicators with axillary lymph node metastasis in invasive breast cancer
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Invasive breast cancer (IBC) is the most common malignancy in women worldwide, and axillary lymph node status remains the strongest predictor of survival. Sentinel lymph node biopsy (SLNB) is the reference standard, but it is invasive, expensive, and carries appreciable morbidity. Reliable pre-operative, non-invasive markers are therefore urgently needed. This study aimed to investigate the correlation between ultrasound features, immunohistochemical indicators, and axillary lymph node metastasis in IBC. Methods: This study retrospectively analysed the data of 125 patients with IBC (diagnosed by preoperative core-needle biopsy or intraoperative pathology) who underwent surgical resection between January 2019 and December 2022. Patients were divided into metastatic (n=65) and non-metastatic (n=60) groups based on axillary lymph node metastasis status. Data were collected and compared. Results: Among the 125 patients, there were 26 (21%) luminal A, 58 (46%) luminal B, 20 (16%) human epidermal growth factor receptor 2 (HER2) overexpression, and 21 (17%) triple-negative types. Significant differences were found between the two groups in tumour blood flow grades (P<0.001), axillary lymph node ultrasound (P<0.001), tumour sizes (P<0.001), and Kiel-67 (Ki-67) positivity (P=0.028). Regression analysis showed that large tumour size [odds ratio (OR) =9.776; 95% confidence interval (CI): 2.111-45.266] and abnormal axillary lymph node ultrasound (OR =35.800; 95% CI: 7.637-167.846) were risk factors for metastasis. Conclusions: Tumour size, blood flow grade, Ki-67 expression, and axillary lymph node ultrasound diagnosis are correlated with axillary lymph node metastasis in IBC. Maximum tumour diameter ≥20 mm and abnormal axillary lymph node ultrasound are significant risk factors.
Institutions: Northern Jiangsu People's Hospital, Yangzhou University
Language: English
Subfield: Pathology and Forensic Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7117681469
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