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预测乳腺癌肺转移患者生存情况的有效工具:基于监测、流行病学与结果(SEER)构建的列线图

An effective tool for predicting survival in breast cancer patients with lung metastasis: Nomograms constructed based on SEER.

作者信息

Wang WenYi, Liu JiaJing, Chen YuQiu, Xu XiaoFan, Huo LiQun, Wang XuLin, Gu Jun

机构信息

Research Institute of General Surgery, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, China.

Department of General Surgery, Jinling Hospital, Nanjing Medical University, Nanjing, China.

出版信息

Front Surg. 2023 Jan 6;9:939132. doi: 10.3389/fsurg.2022.939132. eCollection 2022.

Abstract

BACKGROUND & OBJECTIVES: An effective tool for forecasting the survival of BCLM is lacking. This study aims to construct nomograms to predict overall survival (OS) and breast cancer-specific survival (BCSS) in breast cancer patients with lung metastasis, and to help clinicians develop appropriate treatment regimens for breast cancer lung metastasis (BCLM) individuals.

METHODS

We gathered clinical data of 2,537 patients with BCLM between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Cox regression analysis was employed to identify independent prognostic parameters for BCLM, which were integrated to establish nomograms by R software. The discriminative ability and predictive accuracy of the nomograms were assessed using the concordance index (C-index), receiver operating characteristic (ROC) curves, and calibration plots. Kaplan-Meier analyses were applied to evaluate the clinical utility of the risk stratification system and investigate the survival benefit of primary site surgery, chemotherapy, and radiotherapy for BCLM patients.

RESULTS

Two nomograms shared common prognostic indicators including age, marital status, race, laterality, grade, AJCC T stage, subtype, bone metastasis, brain metastasis, liver metastasis, surgery, and chemotherapy. The results of the C-index, ROC curves, and calibration curves demonstrated that the nomograms exhibited an outstanding performance in predicting the prognosis of BCLM patients. Significant differences in the Kaplan-Meier curves of various risk groups corroborated the nomograms' excellent stratification. Primary site surgery and chemotherapy remarkably improved OS and BCSS of BCLM patients whether the patients were at low-risk or high-risk, but radiotherapy did not.

CONCLUSIONS

We successfully developed prognostic stratification nomograms to forecast prognosis in BCLM patients, which provide important information for indicating prognosis and facilitating individualized treatment regimens for BCLM patients.

摘要

背景与目的

目前缺乏预测乳腺癌肺转移(BCLM)患者生存情况的有效工具。本研究旨在构建列线图,以预测发生肺转移的乳腺癌患者的总生存期(OS)和乳腺癌特异性生存期(BCSS),并帮助临床医生为BCLM患者制定合适的治疗方案。

方法

我们从监测、流行病学和最终结果(SEER)数据库中收集了2010年至2015年间2537例BCLM患者的临床数据。采用Cox回归分析确定BCLM的独立预后参数,并通过R软件将这些参数整合以建立列线图。使用一致性指数(C指数)、受试者工作特征(ROC)曲线和校准图评估列线图的辨别能力和预测准确性。应用Kaplan-Meier分析评估风险分层系统的临床实用性,并研究原发部位手术、化疗和放疗对BCLM患者的生存获益。

结果

两个列线图共享的预后指标包括年龄、婚姻状况、种族、侧别、分级、美国癌症联合委员会(AJCC)T分期、亚型、骨转移、脑转移、肝转移、手术和化疗。C指数、ROC曲线和校准曲线的结果表明,列线图在预测BCLM患者预后方面表现出色。各风险组的Kaplan-Meier曲线存在显著差异,证实了列线图的良好分层效果。无论患者处于低风险还是高风险,原发部位手术和化疗均显著改善了BCLM患者的OS和BCSS,但放疗没有。

结论

我们成功开发了预后分层列线图来预测BCLM患者的预后,这为提示预后和促进BCLM患者的个体化治疗方案提供了重要信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4dad/9852616/9b100bdf36a0/fsurg-09-939132-g001.jpg

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