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基于 SEER 数据库的人群研究:列线图预测透明细胞肾细胞癌患者的癌症特异性生存。

Nomogram for predicting cancer-specific survival of patients with clear-cell renal cell carcinoma: a SEER-based population study.

机构信息

Department of Foot and Ankle Surgery, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi Province, China.

出版信息

Gen Physiol Biophys. 2022 Nov;41(6):591-601. doi: 10.4149/gpb_2022040.

DOI:10.4149/gpb_2022040
PMID:36454119
Abstract

This study was aimed to develop a nomogram for predicting the cancer-specific survival (CSS) of patients with clear-cell renal cell carcinoma (ccRCC). Based on the Surveillance, Epidemiology, and End Results (SEER) database, 24,477 patients diagnosed with ccRCC between 2010 and 2015 were collected. They were randomly divided into a training cohort (n = 17,133) and a validation cohort (n = 7,344). Univariate and multivariate Cox regression analyses were performed in the training cohort to identify independent prognostic factors for construction of nomogram. Then, the nomogram was used to predict the 3- and 5-year CSS. The performance of nomogram was evaluated by using concordance index (C-index), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA). Moreover, the nomogram and tumor node metastasis (TNM) staging system (AJCC 7th edition) were compared. Eleven variables were screened to develop the nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) and the calibration plots indicated satisfactory ability of the nomogram. Compared with the AJCC 7th edition of TNM stage, C-index, NRI, and IDI showed that the nomogram had improved performance. Furthermore, the 3- and 5-year DCA curves of nomogram yielded more net benefits than the AJCC 7th edition of TNM stage in both the training and validation sets. We developed and validated a nomogram for predicting the CSS of patients with ccRCC, which was more precise than the AJCC 7th edition of TNM staging system.

摘要

本研究旨在开发一个列线图,用于预测透明细胞肾细胞癌(ccRCC)患者的癌症特异性生存(CSS)。基于监测、流行病学和最终结果(SEER)数据库,收集了 2010 年至 2015 年间诊断为 ccRCC 的 24477 例患者。他们被随机分为训练队列(n = 17133)和验证队列(n = 7344)。在训练队列中进行单因素和多因素 Cox 回归分析,以确定构建列线图的独立预后因素。然后,使用列线图预测 3 年和 5 年 CSS。通过一致性指数(C-index)、净重新分类改善(NRI)、综合判别改善(IDI)、校准曲线和决策曲线分析(DCA)评估列线图的性能。此外,还比较了列线图和肿瘤淋巴结转移(TNM)分期系统(AJCC 第 7 版)。筛选出 11 个变量来开发列线图。受试者工作特征(ROC)曲线下面积(AUC)和校准图表明该列线图具有良好的能力。与 AJCC 第 7 版 TNM 分期相比,C-index、NRI 和 IDI 表明列线图具有更好的性能。此外,在训练集和验证集中,3 年和 5 年 DCA 曲线表明列线图比 AJCC 第 7 版 TNM 分期具有更多的净收益。我们开发并验证了一个用于预测 ccRCC 患者 CSS 的列线图,该列线图比 AJCC 第 7 版 TNM 分期系统更准确。

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