• Department of Breast Surgery, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan 646000, P. R. China;
ZUO Huaiquan, Email: 13982772996@163.com
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Objective To explore the risk factors affecting sentinel lymph node (SLN) metastasis in patients with N0 early-stage breast cancer and establish a predictive model for SLN metastasis, so as to assist in the decision-making of axillary surgery in clinical practice. Methods The early breast cancer patients who underwent surgical treatment and SLN biopsy at the Affiliated Hospital of Southwest Medical University from September 2020 to December 2023 were selected as the study subjects. The univariate analysis and multivariable logistic regression analysis were adopted to analysis the relevant risk factors of SLN metastasis, then a predictive model evaluating the risk of SLN metastasis was constructed. The receiver operating characteristic (ROC) curve and the area under ROC curve (AUC) was used to assess the predictive performance of risk factors of SLN metastasis. Results A total of 351 patients with early breast cancer patients who met the inclusion criteria were collected, 136 of whom with SLN metastasis, the SLN metastasis rate was 38.7%. The results of the multivariate logistic regression analysis showed that the maximum tumor diameter >2.5 cm, ER positive, Ki-67 value >20%, and vascular invasion were the risk factors for SLN metastasis [maximum tumor diameter: OR(95%CI)=1.897(1.186, 3.034), P=0.008; ER positive: OR(95%CI)=2.721(1.491, 4.967), P=0.001; Ki-67 >20%: OR(95%CI)=1.825(1.125, 2.960), P=0.015; vascular invasion: OR(95%CI)=2.858(1.641, 4.976), P<0.001]. The AUC for the SLN metastasis by these four factors was 0.693, with a sensitivity and specificity of 70.59% and 57.21%, respectively. Conclusions The results from this study suggest that SLN biopsy is recommended to guide postoperative adjuvant treatment strategies for patients with cN0 early stage breast cancer with a maximum tumor diameter >2.5 cm, ER positivity, Ki-67 >20%, and vascular invasion. However, the predictive model constructed based on these four factors in this study has a general ability to distinguish the occurrence of SLN metastasis, then the reasons can be further analyzed in the future.

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