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基于 SEER 数据库和中国队列的早期非小细胞肺癌预后列线图的开发和验证研究。

Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort.

机构信息

Bengbu Medical College Graduate Department, Bengbu, 233000, China.

Department of Cardio-Thoracic Surgery, Affiliated Hospital of Jiaxing University, 314000, Zhejiang, People's Republic of China.

出版信息

BMC Cancer. 2022 Sep 14;22(1):980. doi: 10.1186/s12885-022-10067-8.

Abstract

OBJECTIVE

This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC).

METHODS

For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves.

RESULTS

A Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718-0.735) and 0.721 (95% CI, 0.709-0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691-0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system.

CONCLUSION

We developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions.

摘要

目的

本研究旨在构建一个列线图,以有效预测早期非小细胞肺癌(NSCLC)患者的总生存期(OS)。

方法

在训练和内部验证队列中,共从监测、流行病学和最终结果(SEER)数据库中获得了 26941 例 I 期和 II 期 NSCLC 患者的数据。使用 Cox 比例风险回归模型,根据影响预后的风险因素构建了一个列线图。并从嘉兴第一医院招募了 505 名患者进行外部验证。通过 C 指数和校准曲线评估了列线图的区分度和校准度。

结果

通过单因素和多因素因素分析确定了独立的预后因素后,构建了一个列线图。该列线图在训练队列和内部验证队列中的 C 指数分别为 0.726(95%CI,0.718-0.735)和 0.721(95%CI,0.709-0.734),在外部验证队列中为 0.758(95%CI,0.691-0.825),表明该模型具有良好的区分度。1 年、3 年和 5 年 OS 概率的校准曲线显示了预测和实际生存之间的良好一致性。此外,DCA 分析表明,新模型的净获益明显高于传统的 TNM 分期系统。

结论

我们开发并验证了一个用于早期非小细胞肺癌患者的生存预测模型。这个新的列线图优于传统的 TNM 分期系统,可以指导临床医生做出最佳的临床决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca2c/9476583/2ce52388ff8c/12885_2022_10067_Fig1_HTML.jpg

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