转移性乳腺癌；SEER；列线图；预测；存活," /> 转移性乳腺癌；SEER；列线图；预测；存活,"/> Metastatic breast cancer,SEER,Nomogram model,Prediction,Survival,"/> 基于SEER数据库预测转移性乳腺癌相对长期存活列线图模型构建及验证

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中国癌症防治杂志

中国癌症防治杂志 ›› 2024, Vol. 16 ›› Issue (4): 454-461.doi: 10.3969/j.issn.1674-5671.2024.04.11

• 临床研究 • 上一篇    下一篇

基于SEER数据库预测转移性乳腺癌相对长期存活列线图模型构建及验证

  

  1. 广西医科大学附属肿瘤医院乳腺外科；广西医科大学附属肿瘤医院神经外科
  • 出版日期:2024-08-25 发布日期:2024-08-23
  • 通讯作者: 陈彬洁 E-mail：chenbj6@163.com；韦长元 E-mail：changyuanwei@gxmu.edu.cn
  • 基金资助:
    广西壮族自治区卫生健康委员会自筹课题（Z20210117）

Construction and validation of nomogram model for predicting the relatively long-term survival of metastatic breast cancer based on SEER database

  • Online:2024-08-25 Published:2024-08-23

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摘要： 目的 基于SEER数据库构建并验证转移性乳腺癌患者相对长期存活列线图预测模型。方法 本研究利用SEER数据库中2010—2015年转移性乳腺癌患者的临床病理特征数据，将患者按照7∶3的比例随机分为训练集和验证集，在训练集中进行单因素、多因素Logistic回归分析及列线图模型的构建，在训练集和验证集中绘制受试者工作特征（receiver operating characteristic，ROC）曲线、校准曲线和临床决策曲线评估模型的效能。结果 共纳入6 515例符合标准的转移性乳腺癌患者，其中训练集4 560例及验证集1 955例。训练集中有2 229（48.9%）例为相对长期存活（>24个月）患者，验证集中有970（49.6%）例。多因素Logistic回归分析结果发现年龄、婚姻状态、种族、组织学分级、T分期、N分期、是否脑转移、是否肝转移、是否肺转移、首次诊断至治疗的时间、雌激素受体（estrogen receptor，ER）、孕激素受体（progesterone receptor，PR）、手术方式、分子亚型等临床病理特征是转移性乳腺癌患者相对长期存活的独立影响因素（均P<0.05）。基于此构建的列线图模型在训练集和验证集中的AUC分别为0.738（95%CI：0.724~0.752）和0.745（95%CI：0.723~0.766），校准曲线显示该模型预测结果与实际结果的一致性较好，临床决策曲线显示该模型具有较高的净获益。结论 本研究构建的列线图模型能预测转移性乳腺癌患者的相对长期存活，为临床个体化治疗实践提供辅助决策依据。

关键词: 转移性乳腺癌；SEER；列线图；预测；存活')">">转移性乳腺癌；SEER；列线图；预测；存活

Abstract: Objective To construct and validate a nomogram model for predicting the relatively long⁃term survival in patients with metastatic breast cancer based on the SEER database. Methods The clinicopathological data of patients with metastatic breast cancer from 2010 to 2015 in SEER database were randomly divided into a training set and a validation set in a 7∶3 ratio. Univariable and multivariable logistic regression analyses were performed and the nomogram model was constructed in the training set. The receiver operating characteristic (ROC) curve, calibration curve, and clinical decision curve were plotted for both the training and validation sets to evaluate the efficacy of the model. Results A total of 6,515 eligible patients with metastatic breast cancer were included, with 4,560 patients in the training set and 1,955 patients in the validation set. In the training set, 2,229 (48.9%) patients were relatively long⁃term survivors (>24 months), and in the validation set, 970 (49.6%) patients were relatively long⁃term survivors. Multivariable Logistic regression analysis showed that age, marital status, race, histological grade, T stage, N stage, brain metastasis, liver metastasis, lung metastasis, time from initial diagnosis to treatment, estrogen receptor (ER) status, progesterone receptor (PR) status, surgical approach and molecular subtype were all independent factors which could affect the relatively long⁃term survival in patients with metastatic breast cancer (all P<0.05). The AUCs of the nomogram model in the training and validation sets were 0.738 (95%CI: 0.724-0.752) and 0.745 (95%CI: 0.723-0.766), respectively. The calibration curve showed a good consistency between the  predicted outcomes and actual outcomes of the model, and the clinical decision curve showed a high net benefit of the model. Conclusions The nomogram model constructed in this study can predict the relatively long⁃term survival of patients with metastatic breast cancer, providing an auxiliary decision⁃making basis for clinical practice and supporting individualized treatment decisions.

Key words: Metastatic breast cancer')">Metastatic breast cancer, SEER, Nomogram model, Prediction, Survival

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  • 引用本文

    张文海, 练斌, 侯秦汉, 梁鑫光, 杨秋娇, 梁玲, 陈彬洁, 韦长元. 基于SEER数据库预测转移性乳腺癌相对长期存活列线图模型构建及验证[J]. 中国癌症防治杂志, 2024, 16(4): 454-461.

    ZHANG Wenhai, LIAN Bin, HOU Qinhan, LIANG Xinguang, YANG Qiujiao, LIANG Ling, CHEN Binjie, WEI Changyuan. Construction and validation of nomogram model for predicting the relatively long-term survival of metastatic breast cancer based on SEER database[J]. Chinese Journal of Oncology Prevention and Treatment, 2024, 16(4): 454-461.