基于SEER数据库构建微浸润乳腺癌腋窝淋巴结转移风险预测模型  

Establishment of Risk-Prediction Model for Axillary Lymph-Node Metastasis in Microinvasive Breast Cancer Based on SEER Database

作　　者：刘程浩 鲁婷 钱芳 徐元兵 胡超华[1] 沈浩元[1] LIU Chenghao;LU Ting;QIAN Fang;XU Yuanbing;HU Chaohua;SHEN Haoyuan(Department of Thyroid and Breast Surgery,Xiaogan Hospital Affiliated to Wuhan University of Science and Technology(Xiaogan Central Hospital),Xiaogan 432000,China;Department of Gastroenterology,Xiaogan Hospital Affiliated to Wuhan University of Science and Technology(Xiaogan Central Hospital),Xiaogan 432000,China;Postgr-aduate Training Base of Xiaogan Central Hospital of Jinzhou Medical University,Xiaogan 432000,China)

机构地区：[1]武汉科技大学附属孝感医院(孝感市中心医院)甲状腺乳腺外科,孝感432000 [2]武汉科技大学附属孝感医院(孝感市中心医院)消化内科,孝感432000 [3]锦州医科大学孝感市中心医院研究生培养基地,孝感432000

出　　处：《肿瘤防治研究》2024年第9期750-755,共6页Cancer Research on Prevention and Treatment

基　　金：湖北省科技厅大健康领域重点项目(2022BCE041);湖北省孝感市自然科学基金(XGKJ2021010048)。

摘　　要：目的分析微浸润乳腺癌(MIBC)患者腋窝淋巴结转移(ALNM)的影响因素,构建MIBC患者同侧ALNM风险预测模型。方法通过SEER数据库检索并筛选出2010-2015年病理确诊的4475例原发MIBC女性患者作为建模组,另筛选SEER数据库中2018-2020年病理确诊的2266例原发MIBC女性患者作为外部验证组,收集入组MIBC患者的临床病理资料,单因素分析筛选出影响MIBC患者ALNM的因素,将有统计学意义的变量纳入多因素Logistic回归分析,筛选出影响MIBC患者ALNM的独立影响因子并建立列线图,绘制受试者工作特征(ROC)曲线计算曲线下面积(AUC),绘制校准曲线,并行Hosmer-Lemeshow拟合优度检验进行模型评价。结果纳入6741例MIBC患者中发生同侧ALNM患者为309例,比例约为4.58%。建模组单因素分析显示:年龄、种族、组织学分级、病理类型、分子亚型、边侧与MIBC患者ALNM相关(P<0.05)。多因素分析结果显示:≤40岁、黑种人、组织学分级Ⅱ级及Ⅲ级、原发于右侧的MIBC发生ALNM的风险更高(P<0.05),分子亚型是MIBC患者ALNM的独立影响因素,但HR+HER2+、HR-HER2+、HR-HER2-三种分子亚型MIBC与HR+HER2-亚型间ALNM风险差异均无统计学意义。利用上述变量建立预测列线图,得出建模组AUC为0.716,(95%CI:0.682~0.750),最佳截断值为0.045,其敏感度为0.733,特异性为0.608。将新建的列线图模型用于验证组,其AUC为0.722(95%CI:0.667~0.777)。建模组及验证组的校准曲线Hosmer-Lemeshow拟合优度检验均P>0.05。结论通过SEER数据库建立的MIBC患者ALNM风险预测模型,预测能力较好,有望为临床实践提供参考。Objective To analyze the factors influencing axillary lymph-node metastasis(ALNM)in microinvasive breast cancer(MIBC)patients,as well as to establish the risk-prediction model of ipsilateral ALNM in MIBC patients.Methods A total of 4475 primary female MIBC diagnosed by pathology from 2010 to 2015 were searched and screened from the SEER database.The obtained data were used to establish a prediction model for ALNM of MIBC.A total of 2266 primary female MIBC patients diagnosed by pathology from 2018 to 2020 in the SEER database were screened as the external validation cohort.The clinicopathological data of the enrolled MIBC patients were collected.Univariate analysis was used to screen out the factors affecting ALNM in MIBC patients.Statistically significant variables in univariate analysis were included in multivariate logistic regression analysis.The independent factors influencing ALNM in MIBC patients were screened out,and a nomogram was established.The area under the curve(AUC)was calculated by plotting the ROC curve.After plotting the calibration curve,the model was evaluated by Hosmer-Lemeshow goodness-of-fit test.Results A total of 309 patients were diagnosed with ipsilateral ALNM among the 6741 MIBC patients,accounting for about 4.58%.Univariate analysis of the modeling group showed that age,ethnicity,histological grade,pathological type,molecular subtype,and lateral side were associated with ALNM in MIBC patients(P<0.05).Results of multivariate analysis showed that the risk of ALNM was higher in MIBC patients≤40 years old,black people,histological gradeⅡandⅢ,and primary right side(P<0.05).Subtype is an independent factor influencing ALNM in MIBC patients.However,the difference in ALNM risk was not statistically significant between the subtype of HR+HER2+,HR-HER2+,HR-HER2-and HR+HER2-subtypes.The AUC of the modeling group was 0.716(95%CI:0.682-0.750),the best cut-off value was 0.045,the sensitivity was 0.733,and the specificity was 0.608.The newly established nomogram model was used for the validatio

关 键 词：SEER数据库 微浸润乳腺癌 腋窝淋巴结转移 预测模型 

分 类 号：R737.9[医药卫生—肿瘤]