【摘要】 目的：探讨早期乳腺癌非前哨淋巴结(NSLN)转移状态预测模型的预测价值。方法：回顾性分析2015年6月-2021年7月揭阳市人民医院收治的早期乳腺癌患者120例，由纳排标准筛选后最终纳入104例，并依据NSLN是否发生转移将其分为未转移组(67例)和转移组(37例)进行早期乳腺癌NSLN转移状态模型的建立。依据χ~2检验、秩和检验比较组间不同病理特征的差异，采用单因素和多因素Logistic回归模型建立早期乳腺癌NSLN转移状态预测模型，并以预测概率做受试者工作特征(ROC)曲线，以曲线下面积(AUC)值评估模型预测能力。结果：两组年龄、月经状态、组织分化级别、是否多灶性、是否伴脉管癌栓、病程、雌激素受体(ER)、孕激素受体(PR)、人表皮生长因子受体2(HER2)、细胞增殖抗原Ki-67、SLN转移灶大小比较，差异无统计学意义(P>0.05)；转移组肿瘤直径>2 cm、SLN阳性数≥3枚、SLN阳性数/活检数>0.5的比例均高于未转移组(P<0.05)。多因素Logistic回归分析结果显示肿瘤直径>2 cm、SLN阳性数≥3枚、SLN阳性数/活检数>0.5为NSLN转移的独立危险因素(P<0.05)；ROC曲线结果显示，敏感度为67.60%，特异度为79.10%，AUC值为0.821。结论：以肿瘤直径、SLN阳性数、SLN阳性数/活检数作为自变量构建早期乳腺癌NSLN转移状态预测模型具有较高的预测价值。更多还原

【Abstract】 Objective:To explore the predictive value of non-sentinel lymph node (NSLN) metastasis prediction model in early breast cancer.Method:A retrospective analysis of 120 patients with early breast cancer admitted to Jieyang People’s Hospital from June 2015 to July 2021.After screening by the admission criteria,104 cases were finally included,they were divided into non-metastatic group (67 cases) and metastatic group (37 cases) according to whether or not NSLN had metastasized,so as to establish the metastatic status model of early breast cancer NSLN.The Chi-square and rank sum test were used to compare the differences of different pathological features between groups,the univariate and multivariate Logistic regression models were used to establish a prediction model for NSLN metastasis in early breast cancer,and the predictive probability was used as the receiver operating characteristic curve (ROC),and use the area under the curve (AUC) value was used to evaluate the predictive ability of the model.Result:There were no significant differences between the two groups in age,menstrual state,grade of tissue differentiation,whether there were multiple lesions,whether there were vascular cancer thrombus,disease course,estrogen receptor (ER),progesterone receptor (PR),human epidermal growth factor receptor 2 (HER2),cell proliferation antigen Ki-67 and SLN metastasis size (P>0.05).The ratio of metastatic tumors >2 cm,SLN positive number ≥3,and SLN positive number/biopsy number >0.5 in metastatic group were higher than those in non-metastatic group (P<0.05).Multivariate Logistic regression results showed that tumor size >2 cm,number of SLN positives ≥3,and number of SLN positives/number of biopsies >0.5 were independent risk factors for NSLN metastasis (P<0.05).ROC curve showed that the sensitivity was 67.60%,the specificity was 79.10% and the AUC value was 0.821.Conclusion:Constructing an early breast cancer NSLN metastasis prediction model with tumor size,number of SLN positives,and number of SLN positives/biopsy as independent variables has high predictive value.更多还原