关键词: 乳腺癌, 前哨淋巴结转移, 预测因素, 腋窝超声, 预测模型

Abstract:

Objective To develop a multivariate predictive nomogram to identify high-risk cohorts for sentinel lymph node （SLN） metastasis among cT1-2N0 breast cancer patients with preoperatively normal axillary ultrasound （AUS）， thereby providing a reference for personalized axillary management. Methods A retrospective analysis was conducted on the clinicopathological and ultrasonographic data of 427 patients diagnosed with invasive breast cancer who received treatment at Ward 4 （Breast Unit）， Department of General Surgery， Liuzhou Workers' Hospital， between January 2018 and December 2023. Univariate correlation analysis and multivariate logistic regression analysis were employed to identify independent risk factors associated with SLN metastasis. The accuracy and predictive performance of the nomogram were assessed using receiver operating characteristic （ROC） curve analysis. Results Our study enrolled 427 women diagnosed with clinical T1-2N0 breast cancer who underwent preoperative AUS with normal findings. Among these patients， 47 cases （11.0%） exhibited sonographically normal axillary lymph nodes， whereas 380 cases （89.0%） showed non-visualized lymph nodes. SLN metastasis， confirmed by postoperative pathological examination， was identified in 78 patients （18.3%）. Univariate analysis revealed that estrogen receptor （ER） status， maximal tumor diameter， tumor location， lymphovascular invasion （LVI）， and perineural invasion （PNI） were significantly associated with the presence of SLN metastasis （P < 0.05）. Multivariate logistic regression analysis further identified the following independent high-risk factors for SLN metastasis： tumor location in the upper outer quadrant （OR = 4.118， 95% CI = 1.349 ~ 12.571）， tumor size greater than 2 cm （OR = 2.246， 95% CI = 1.252 ~ 4.029）， presence of LVI （OR = 4.477， 95% CI = 2.207 ~ 9.081）， and presence of PNI （OR = 3.013， 95% CI = 1.573 ~ 5.771） （all P < 0.05）. Ultrasonographic features of axillary lymph nodes—including their positivity status， short-axis diameter， and numerical count—did not show a statistically significant association with the SLN metastatic burden （P ≥ 0.05）. However， these features demonstrated a statistically significant correlation with the pathological nodal stage （pN-stage） classification （P < 0.05）. In patients with 1 ~ 2 positive sentinel lymph nodes， sonographic characteristics of axillary lymph nodes （including status， maximum diameter， minimum diameter， and numerical count） did not exhibit a significant association with either axillary lymph node metastatic burden or pN-stage classification （all P ≥ 0.05）. The area under the receiver operating characteristic curve （AUC） for the predictive nomogram was 0.702 （95% CI： 0.651 ~ 0.749， P < 0.0001）， with a sensitivity of 78.21% and specificity of 59.12%. Conclusions Tumor location in the upper outer quadrant， tumor size greater than 2 cm， LVI， and PNI were identified as significant independent risk factors for SLN metastasis among patients with clinical T1-2N0 breast cancer who underwent preoperative AUS with normal findings. Furthermore， from the perspective of pN-stage stratification， omission of axillary lymph node dissection （ALND） appears to be clinically feasible for the majority of cT1-2N0 patients with 1 ~ 2 metastatic SLNs. However， preoperative ultrasonographic characteristics of lymph nodes demonstrate limited predictive value for axillary lymph node （ALN） metastatic burden or pN-stage progression.

Key words: breast cancer, sentinel lymph node metastasis, predictors, axillary ultrasonography, predictive nomogram