初诊乳腺癌肝转移患者列线图预后模型的构建
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1.陕西省人民医院 肿瘤外科,陕西 西安 710068;2.西安医学院 研究生处,陕西 西安 710021;3.陕西省肿瘤医院 乳腺病院,陕西 西安 710061

作者简介:

宋张骏,陕西省人民医院主任医师,主要从事触诊阴性乳腺癌方面的研究。

基金项目:

陕西省西安市科技计划基金资助项目[2019115213YX007SF040(3)];陕西省卫生健康科研基金资助项目(2018D029);陕西省中医药管理科研基金资助项目(2019-ZZ-JC027)。


Construction of a prognostic nomogram model for newly diagnosed patients with breast cancer liver metastases
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1.Department of Surgical Oncology, Shaanxi People's Hospital, Xi'an 710068, China;2.Graduate Office of Xi'an Medical University, Xi'an 710021, China;3.Department of Breast Disease, Shaanxi Cancer Hospital, Xi'an 710061, China

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    摘要:

    背景与目的 乳腺癌肝转移(BCLM)患者预后较差,其预后因不同因素而有较大差别。关于BCLM预后的研究很少,且目前缺乏准确预测BCLM的预后的手段。因此,本研究构建列线图来预测初诊BCLM患者的3、5年总生存率(OS)和特异性生存率(CSS),以期为临床提供参考。方法 在SEER数据库中提取2010—2016年的初诊为BCLM患者资料,根据纳入和排除标准,严格筛选后纳入研究病例共1 994例,按7∶3比例随机分配为建模组(1 398例)和验证组(596例),将单因素分析差异有统计学意义的变量纳入多因素Cox回归模型进行分析,得到影响BCLM患者生存情况的独立危险因素。基于影响BCLM患者预后的独立危险因素构建预测OS和CSS的列线图模型,通过一致性指数和校正曲线评估列线图的可靠性。结果 年龄、种族、婚姻、组织学分级、激素受体状态、手术、化疗、骨转移、脑转移、肺转移是BCLM患者预后的独立影响因素(均P<0.05),这些因素均用于构建列线图预后模型,建模组和验证组OS的一致性指数为0.709、0.731,建模组和验证组CSS的一致性指数为0.709、0.732。模型的校正曲线显示该列线图的生存率预测值与实际观测值之间具有良好的一致性。结论 所构建的列线图预后模型能够准确预测初诊BCLM患者预后状态,为临床医生制定个体化的治疗方案提供参考。

    Abstract:

    Background and Aims The prognosis of patients with breast cancer liver metastasis (BCLM) is poor, and the prognosis is often different due to different factors. There are few studies on the prognosis of BCLM, and still a lack of accurate prediction method for the prognosis of BCLM so far. Therefore, this study was conducted to construct a nomogram to predict the 3- and 5-year overall survival (OS) and cancer specific survival (CSS) of newly diagnosed BCLM patients, so as to provide a reference for clinical use.Methods The data of patients with initial diagnosis of BCLM between 2010 and 2016 were retrieved from the SEER database. Strictly following the inclusion and exclusion criteria, 1 994 patients were selected and randomly divided into model group (n=1 398) and validation group (n=596) at a ratio of 7∶3. The variables with statistical significance in univariate analysis were included in the multivariate Cox regression model, and the independent risk factors affecting the survival of BCLM patients were obtained. A nomogram for predicting OS and CSS was established based on the independent risk factors affecting the prognosis of BCLM patients. The reliability of the nomogram was evaluated by concordance index (C-index) and calibration curve.Results Age, race, marriage, grade, status of hormone receptors, surgery, chemotherapy, bone metastasis, brain metastasis and lung metastasis were independent prognostic factors for patients with BCLM (all P<0.05). Based on these factors, the nomogram was successfully constructed. The C-index of OS in model and validation groups were 0.709 and 0.731, and the C-index of CSS in model and validation groups were 0.709 and 0.732, respectively. Calibration curves also showed an excellent agreement between actual survival and nomogram prediction.Conclusion The established nomogram can accurately predict the prognosis in patients with initial diagnosis of BCLM. It may be helpful for clinicians to make individualized treatment plans.

    表 3 建模组1 398例患者OS和CSS的多因素Cox回归分析Table 3 Multivariate Cox regression analysis of OS and CSS in 1 398 patients in model group
    表 2 建模组1 398例患者OS和CSS的单因素分析Table 2 Univariate analysis of OS and CSS in 1 398 patients in model group
    表 1 建模组和验证组患者的临床病理特征[n(%)]Table 1 Clinicopathological characteristics of patients in model and validation groups [n (%)]
    图1 SEER数据库中BCLM患者筛选流程图Fig.1 Screening process of BCLM patient in SEER database
    图2 BCLM患者的3、5年OS的列线图预后模型Fig.2 Nomogram prediction model of 3- and 5-year OS in patients with BCLM
    图3 BCLM患者的3、5年CSS的列线图预后模型Fig.3 Nomogram prediction model of 3 -and 5-year CSS in patients with BCLM
    图4 建模组列线图的校准曲线 A:3年OS校准图;B:5年OS校准图;C:3年CSS校准图;D:5年CSS校准图Fig.4 The calibration curves of nomogram in model group A: 3-year OS calibration curve; B: 5-year OS calibration curve; C: 3-year CSS calibration curve; D: 5-year CSS calibration curve
    图5 验证组列线图的校准曲线 A:3年OS校准图;B:5年OS校准图;C:3年CSS校准图;D:5年CSS校准图Fig.5 The calibration curves of nomogram in validation group A: 3-year OS calibration curve; B: 5-year OS calibration curve; C: 3-year CSS calibration curve; D: 5-year CSS calibration curve
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宋张骏,刘奋德,王虎霞,王星光,界露.初诊乳腺癌肝转移患者列线图预后模型的构建[J].中国普通外科杂志,2021,30(11):1274-1284.
DOI:10.7659/j. issn.1005-6947.2021.11.002

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  • 收稿日期:2021-03-21
  • 最后修改日期:2021-05-10
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  • 在线发布日期: 2021-12-24