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中华乳腺病杂志(电子版) ›› 2026, Vol. 20 ›› Issue (04) : 228 -235. doi: 10.3877/cma.j.issn.1674-0807.2026.04.005

论著

HER-2阳性乳腺癌患者复发转移的影响因素及风险预测模型的构建
苏金铭1,2, 田萍3, 李青林1, 马静4, 宋伟伟5, 刘博文2, 曹晓莹2, 薛玲1, 王文军1,2,()   
  1. 1 063200 唐山,华北理工大学公共卫生学院
    2 262500 潍坊,潍坊护理职业学院党政办公室
    3 262500 潍坊,潍坊市益都中心医院药学部
    4 250036 淄博,淄博市中心医院肿瘤内科
    5 272067 济宁,济宁医学院附属医院乳腺甲状腺外科
  • 收稿日期:2025-10-21 出版日期:2026-08-01
  • 通信作者: 王文军
  • 基金资助:
    北京爱谱癌症患者关爱基金(24/107-4387)

Influencing factors of recurrence and metastasis in HER-2 positive breast cancer patients and construction of prediction model

Jinming Su1,2, Ping Tian3, Qinglin Li1, Jing Ma4, Weiwei Song5, Bowen Liu2, Xiaoying Cao2, Ling Xue1, Wenjun Wang1,2,()   

  1. 1 School of Public Health, North China University of Science and Technology, Tangshan 063200, China
    2 Office of Party and Administration Affairs, Weifang Nursing Vocational College, Weifang 262500, China
    3 Department of Pharmacy, Weifang Yidu Central Hospital, Weifang 262500, China
    4 Department of Medical Oncology, Zibo Central Hospital, Zibo 255036, China
    5 Department of Breast and Thyroid Surgery, Affiliated Hospital of Jining Medical University, Jining 272067, China
  • Received:2025-10-21 Published:2026-08-01
  • Corresponding author: Wenjun Wang
引用本文:

苏金铭, 田萍, 李青林, 马静, 宋伟伟, 刘博文, 曹晓莹, 薛玲, 王文军. HER-2阳性乳腺癌患者复发转移的影响因素及风险预测模型的构建[J/OL]. 中华乳腺病杂志(电子版), 2026, 20(04): 228-235.

Jinming Su, Ping Tian, Qinglin Li, Jing Ma, Weiwei Song, Bowen Liu, Xiaoying Cao, Ling Xue, Wenjun Wang. Influencing factors of recurrence and metastasis in HER-2 positive breast cancer patients and construction of prediction model[J/OL]. Chinese Journal of Breast Disease(Electronic Edition), 2026, 20(04): 228-235.

目的

明确HER-2阳性乳腺癌患者复发转移的影响因素,并构建风险预测模型。

方法

根据纳入与排除标准,回顾性纳入2021年1月至2024年12月山东省4 家三级甲等医院209例HER-2阳性乳腺癌患者作为训练集,纳入2024年1月至2025年5月山东省2家三级甲等医院的121例HER-2阳性乳腺癌患者为外部验证集,收集患者的临床资料进行分析。通过单因素分析、最小绝对收缩与选择算子(LASSO)筛选预测因子,经多因素Logistic回归分析HER-2阳性乳腺癌患者复发转移的影响因素,并构建风险预测模型(列线图),采用受试者操作特征(ROC)曲线、校准曲线及决策曲线分析(DCA)评价模型的区分度、校准度与临床实用性。

结果

LASSO回归最终筛选出7个预测变量:年龄、确诊时间、肿瘤长径、家族史、淋巴水肿、完成靶向治疗、完成化疗。多因素Logistic回归分析结果显示,确诊时间≥1年(OR=2.520,95%CI:1.017~6.245,P=0.046)、肿瘤长径>5 cm(OR=2.998,95%CI:1.209~7.431,P=0.018)是HER-2阳性乳腺癌患者复发转移的危险因素。年龄≥50岁(OR=0.366,95%CI:0.149~0.898,P=0.028)、完成靶向治疗(OR=0.334,95%CI:0.128~0.872,P=0.025)、完成化疗(OR=0.028,95%CI:0.005~0.150,P=0.001)是HER-2阳性乳腺癌患者复发转移的保护因素。基于上述5个影响因素构建列线图。训练集模型ROC曲线的AUC=0.865(95%CI:0.808~0.922),特异度为0.963;Hosmer-Lemeshow 检验结果显示预测模型的校准度较好(χ2=4.632,P=0.462)。外部验证集的AUC=0.817(95%CI:0.715~0.919),特异度为0.946,Hosmer-Lemeshow检验结果显示预测模型的校准度较好(χ2=6.833、P=0.555)。DCA分析显示,在0.2~0.8的风险阈值区间内,应用该模型可获得稳定较好的临床净效益。

结论

患者年龄、确诊时间、肿瘤长径、完成化疗及靶向治疗是HER-2阳性乳腺癌患者复发转移的影响因素。结合上述变量构建的预测模型能够为临床个体化风险评估提供参考依据。

Objective

To identify influencing factors for recurrence and metastasis in patients with HER-2 positive breast cancer, and to establish a risk prediction model.

Methods

According to the inclusion and exclusion criteria, a total of 209 HER-2 positive breast cancer patients from four tertiary hospitals in Shandong Province between January 2021 and December 2024 were retrospectively enrolled as the training set, and 121 patients from two tertiary hospitals between January 2024 and May 2025 were included as the external validation set. The clinicopathological data of patients were collected and analyzed. Univariate analysis and LASSO regression were performed to screen for predictive factors, and multivariate logistic regression was adopted to determine the final variables for constructing a nomogram. Receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical practicability of the model.

Results

Seven predictive variables were finally screened out by multivariate logistic regression, including age, time since diagnosis, tumor size, family history, lymphedema, completion of targeted therapy and completion of chemotherapy. The results showed that time since diagnosis ≥1 year (OR=2.520, 95%CI: 1.017-6.245, P=0.046) and tumor diameter >5 cm (OR=2.998, 95%CI: 1.209-7.431, P=0.018) were risk factors for recurrence and metastasis in patients with HER-2 positive breast cancer; age ≥50 years (OR=0.366, 95%CI: 0.149-0.898, P=0.028) , completion of targeted therapy (OR=0.334, 95%CI: 0.128-0.872, P=0.025) and completion of chemotherapy (OR=0.028, 95%CI: 0.005-0.150, P=0.001) were protective factors. A nomogram was constructed based on the 5 statistically significant variables. In the training set, the area under the ROC curve (AUC) of the model was 0.865 (95%CI: 0.808-0.922) with a specificity of 0.963; the Hosmer-Lemeshow test yielded a good calibration (χ2=4.632, P=0.462). The AUC of the external validation set was 0.817 (95%CI: 0.715-0.919) with a specificity of 0.946 and the results of Hosmer-Lemeshow test showed a good calibration (χ2=6.833, P=0.555). DCA indicated stable and considerable clinical net benefit by applying this model within the risk threshold range of 0.2-0.8.

Conclusion

Patient age, time since diagnosis, tumor size, chemotherapy completion and targeted therapy completion are influencing factors for recurrence and metastasis in patients with HER-2 positive breast cancer. The prediction model established based on the above-mentioned factors can provide references for individualized clinical risk assessment.

表1 训练集与验证集基线特征比较(例)
表2 HER-2阳性乳腺癌患者复发转移的单因素分析[例]
图1 HER-2阳性乳腺癌患者复发转移的LASSO回归变量筛选正则化路径图 A图为十折交叉验证偏差图;B图为系数正则化路径图
表3 HER-2阳性乳腺癌患者复发转移的自变量赋值表
表4 HER-2阳性乳腺癌患者复发转移的Logistic回归分析结果
图2 HER-2阳性乳腺癌患者复发转移风险的列线图
图3 HER-2阳性乳腺癌患者复发转移预测模型的ROC曲线 A、B图分别为训练集和验证集 注:训练集AUC=0.865(95%CI:0.808~0.922);验证集AUC=0.817(95%CI:0.715~0.919)
图4 HER-2阳性乳腺癌患者复发转移预测模型的校准曲线 A、B图分别为训练集和验证集
图5 HER-2阳性乳腺癌患者复发转移预测模型的DCA曲线 A、B图分别为训练集和验证集
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