Assessing the Relationship among Tumor Size, Lymph Node Status, and ER/PR/HER2 Expression in Patients with Breast Cancer.

This study aims to explore the relationship between tumor size, lymph node status, and ER/PR/HER2 expression in breast cancer patients. A total of 117 breast cancer patients who underwent surgery at our hospital were selected as the research objects. All patients underwent ipsilateral axillary lymph node dissection or sentinel lymph node biopsy during surgery. Pathological data and ultrasound features of primary lesions were collected. Univariate and multivariate logistic regression analyses were performed to evaluate the relationship between tumor size, lymph node status, and ER/PR/HER2 expression, as well as to identify the risk factors for lymph node metastasis in breast cancer patients. Among the 117 patients, 48 were positive for ipsilateral axillary lymph node metastasis and 69 were negative. Univariate analysis showed no significant correlation between age, PR status, molecular subtype, and lymph node metastasis (P > 0.05). Univariate analysis showed that tumor size, pathological type, menopausal status, Ki67 expression, HER2 status, and ER status were significantly associated with lymph node metastasis (P < 0.05). Logistic regression further identified tumor size [odds ratio (OR) = 1.809, 95% confidence interval (CI): 1.075-3.428, P = 0.018), pathological type (OR = 2.947, 95% CI: 1.241-7.536, P = 0.012), Ki67 expression (OR = 15.923, 95% CI: 3.219-74.512, P = 0.001), HER2 status (OR = 2.509, 95% CI: 1.586-5.769, P = 0.015), and ER status (OR = 3.226, 95% CI: 1.408-8.277, P = 0.007) as independent risk factors for lymph node metastasis. This study reveals that lymph node metastasis in breast cancer patients is significantly associated with larger tumor size (> 20 mm), invasive tumor type, higher Ki67 expression, HER2 positivity, and ER negativity. These findings emphasize the importance of incorporating these risk factors into clinical assessments to guide individualized treatment planning. By identifying patients with elevated lymph node metastasis risk, clinicians can better tailor treatment strategies to improve patient outcomes and optimize therapeutic interventions.