乳腺癌脑转移患者预后影响因素分析及预测模型的初步构建

熊斯怡; 万安弟; 王成; 章国智; 钟玲; 谭璇妮; 齐晓伟; 张毅

doi:10.16016/j.2097-0927.202307011

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乳腺癌脑转移患者预后影响因素分析及预测模型的初步构建

临床医学 | 更新时间：2026-01-09

- 乳腺癌脑转移患者预后影响因素分析及预测模型的初步构建
- Prognostic factors for breast cancer brain metastasis and primary construction of a prediction model
- 陆军军医大学学报 2023年45卷第18期页码：1974-1982
- 作者机构：
  
  400038 重庆，陆军军医大学(第三军医大学)第一附属医院乳腺甲状腺外科
- 作者简介：
  
  [ 张毅, E-mail: zhangyi1489@sina.com ZHANG Yi, E-mail: zhangyi1489@sina.com
- 基金信息：
  
  重庆市卫生健康委-重庆英才计划项目(CQYC20210303406)
- DOI：10.16016/j.2097-0927.202307011
  中图分类号： R195.4;R737.31;R739.41
- 收稿：2023-07-02，
  
  修回：2023-07-12，
  
  纸质出版：2023-09-30
- 稿件说明：
移动端阅览
熊斯怡, 万安弟, 王成, 等. 乳腺癌脑转移患者预后影响因素分析及预测模型的初步构建[J]. 陆军军医大学学报, 2023,45(18):1974-1982.

Siyi XIONG, Andi WAN, Cheng WANG, et al. Prognostic factors for breast cancer brain metastasis and primary construction of a prediction model[J]. Journal of Army Medical University, 2023, 45(18): 1974-1982.
熊斯怡, 万安弟, 王成, 等. 乳腺癌脑转移患者预后影响因素分析及预测模型的初步构建[J]. 陆军军医大学学报, 2023,45(18):1974-1982. DOI： 10.16016/j.2097-0927.202307011.

Siyi XIONG, Andi WAN, Cheng WANG, et al. Prognostic factors for breast cancer brain metastasis and primary construction of a prediction model[J]. Journal of Army Medical University, 2023, 45(18): 1974-1982. DOI： 10.16016/j.2097-0927.202307011.

摘要

目的

探讨乳腺癌脑转移(breast cancer brain metastasis，BCBM)患者预后影响因素，并构建和验证可评估BCBM患者预后的预测模型。

方法

采用病例-对照研究设计方案。筛选“监测、流行病学和最终结果数据库”(Surveillance，Epidemiology，and End Results，SEER)2016-2020年BCBM患者病例资料1 133例，按照7 ∶3比例随机分配到训练集(793例)和内部验证集(340例)。通过单因素、多因素Cox回归分析确定预后影响因素，并构建列线图(Nomogram图)预测模型。以C指数、ROC曲线和校准曲线对列线图的区分度、预测效能和校准度进行评价。采用陆军军医大学第一附属医院乳腺甲状腺外科2004-2019年收治的BCBM患者(73例)对列线图预测模型进行外部验证。

结果

多因素Cox回归分析确定了年龄、分子分型、手术、放疗、化疗、肺转移、肝转移为独立影响因素(

0.05)，并据此建立列线图预后预测模型。SEER数据库训练集、内部验证集以及本院外部验证集的C指数分别为0.720(95%

：0.674~0.766)、0.705(95%

：0.633~0.777)、0.667(95%

：0.610~0.724)。训练集ROC曲线显示，列线图可以准确预测BCBM患者半年(AUC=0.793)、1年(AUC=0.759)和2年(AUC= 0.724)的生存概率。校准曲线可见预测值与实际观察值具有良好的一致性。

结论

年龄、分子分型、手术、放疗、化疗、肺转移、肝转移是BCBM预后的独立影响因素；据此构建的Nomogram图能有效预测BCBM患者半年、1年和2年的生存概率。

Abstract

Objective

To investigate the prognostic factors of breast cancer brain metastasis (BCBM)

and to construct and validate a prediction model for prognosis of BCBM patients.

Methods

A case-control trial was designed and conducted in this study. A total of 1 133 BCBM patients were screened out from the Surveillance

Epidemiology

and End Results (SEER) database from 2016 to 2020

and were randomly assigned to a training set (

=793) and an internal validation set (

=340) at a ratio of 7 ∶3. The prognostic factors were determined with univariate and multivariate Cox regression analyses

and a nomogram prediction model was constructed. The discrimination

prediction and calibration of the nomograms were evaluated by C-index

receiver operating characteristic (ROC) curve and calibration curve. External validation of the nomogram prediction model was performed in 73 BCBM patients admitted to our hospital

from 2004 to 2019.

Results

Multivariate Cox regression analysis revealed that age

molecular type

surgery

radiotherapy

chemotherapy

lung metastasis and liver metastasis were identified as independent factors (

0.05)

and a prediction model of the nomogram was thus established. The C-index of the SEER training set

internal validation set and external validation set were 0.720 (95%

: 0.674~0.766)

0.705 (95%

: 0.633~0.777) and 0.667 (95%

: 0.610~0.724)

respectively. The ROC curve of the training set showed that our nomogram could accurately predict the survival rate of BCBM patients at 6 months (AUC=0.793)

and 1 (AUC=0.759) and 2 years (AUC=0.724). The predictive values of the calibration curve are in good agreement with the observed values.

Conclusion

Age

molecular type

surgery

radiotherapy

chemotherapy

and lung and liver metastases are independent prognostic factors of BCBM. Our constructed nomogram can effectively predict the 6-month

1-year and 2-year survival probability of BCBM patients.

关键词

Keywords

references

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