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建立并验证预测睾丸癌患者总生存率的列线图。

Development and validation of a nomogram for predicting the overall survival of patients with testicular cancer.

机构信息

Department of Medical Administration, The First Affiliated Hospital of Jinan University, Guangzhou, China.

出版信息

Cancer Med. 2023 Jul;12(14):15567-15578. doi: 10.1002/cam4.6203. Epub 2023 Jun 1.

Abstract

BACKGROUND

The purpose of this study was to develop and validate a nomogram to predict survival in testicular cancer patients.

METHODS

Testicular cancer patients diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were selected for this study. A random sampling method was used to divide patients into training and validation cohorts, which accounted for 30% and 70% of the total sample, respectively. The nomogram was developed using the training cohort and evaluated using the C index, calibration chart, and area under the receiver operating characteristic curve (AUC).

RESULTS

Seven risk factors that affect the survival of testicular cancer patients (AJCC stage, marital status, age at diagnosis, race, SEER historic stage A, surgery status, and origin) were identified using Cox proportional hazard regression analysis. The nomogram has a higher C index (0.897) and AUC when compared with the AJCC staging system. The results of the calibration chart of the nomogram show that the predicted survival of testicular cancer patients at 3, 5, and 10 years after diagnosis is very close to their actual survival.

CONCLUSIONS

We developed and validated a nomogram for predicting the survival rate of testicular cancer patients at 3, 5, and 10 years after diagnosis. This nomogram has better discrimination, calibration, and clinical validity than the AJCC staging system. This indicates that the nomogram can be used to predict the survival of testicular cancer patients effectively, and provide a reference for patient treatment strategies.

摘要

背景

本研究旨在开发和验证一种列线图,以预测睾丸癌患者的生存情况。

方法

本研究选取了 2004 年至 2015 年期间来自监测、流行病学和最终结果(SEER)数据库的睾丸癌患者。采用随机抽样法将患者分为训练队列和验证队列,分别占总样本的 30%和 70%。使用训练队列开发列线图,并通过 C 指数、校准图和接收者操作特征曲线(ROC)下面积(AUC)进行评估。

结果

使用 Cox 比例风险回归分析确定了影响睾丸癌患者生存的七个风险因素(AJCC 分期、婚姻状况、诊断时年龄、种族、SEER 历史分期 A、手术状态和起源)。与 AJCC 分期系统相比,该列线图的 C 指数(0.897)和 AUC 更高。列线图校准图的结果表明,预测睾丸癌患者诊断后 3、5 和 10 年的生存率与实际生存率非常接近。

结论

我们开发并验证了一种预测睾丸癌患者诊断后 3、5 和 10 年生存率的列线图。该列线图具有比 AJCC 分期系统更好的区分度、校准度和临床有效性。这表明该列线图可有效预测睾丸癌患者的生存率,并为患者治疗策略提供参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9351/10417196/f9856cb29316/CAM4-12-15567-g002.jpg

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