Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
Cancer Med. 2024 Apr;13(7):e7111. doi: 10.1002/cam4.7111.
The primary aim of this study was to create a nomogram for predicting survival outcomes in penile cancer patients, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) and a Chinese organization.
Our study involved a cohort of 5744 patients diagnosed with penile cancer from the SEER database, spanning from 2004 to 2019. In addition, 103 patients with penile cancer from Sun Yat-sen Memorial Hospital of Sun Yat-sen University were included during the same period. Based on the results of regression analysis, a nomogram is constructed and validated internally and externally. The predictive performance of the model was evaluated by concordance index (c-index), area under the curve, decision curve analysis, and calibration curve, in internal and external datasets. Finally, the prediction efficiency is compared with the TNM staging model.
A total of 3154 penile patients were randomly divided into the training group and the internal validation group at a ratio of 2:1. Nine independent risk factors were identified, including age, race, marital status, tumor grade, histology, TNM stage, and the surgical approach. Based on these factors, a nomogram was constructed to predict OS. The nomogram demonstrated relatively better consistency, predictive accuracy, and clinical relevance, with a c-index over 0.73 (in the training cohort, the validation cohort, and externally validation cohort.) These evaluation indexes are far better than the TNM staging system.
Penile cancer, often overlooked in research, has lacked detailed investigative focus and guidelines. This study stands as the first to validate penile cancer prognosis using extensive data from the SEER database, supplemented by data from our own institution. Our findings equip surgeons with an essential tool to predict the prognosis of penile cancer better suited than TNM, thereby enhancing clinical decision-making processes.
本研究的主要目的是利用 SEER 数据库和中国机构的数据，创建一个预测阴茎癌患者生存结果的列线图。
我们的研究涉及了 2004 年至 2019 年期间 SEER 数据库中诊断为阴茎癌的 5744 例患者的队列，此外，还纳入了同期中山大学孙逸仙纪念医院的 103 例阴茎癌患者。基于回归分析的结果，构建并内部和外部验证了一个列线图。通过内部和外部数据集的一致性指数（c 指数）、曲线下面积、决策曲线分析和校准曲线评估模型的预测性能。最后，将预测效率与 TNM 分期模型进行比较。
总共 3154 名阴茎癌患者被随机分为训练组和内部验证组，比例为 2:1。确定了 9 个独立的风险因素，包括年龄、种族、婚姻状况、肿瘤分级、组织学、TNM 分期和手术方式。基于这些因素，构建了一个预测 OS 的列线图。列线图表现出相对较好的一致性、预测准确性和临床相关性，c 指数超过 0.73（在训练队列、验证队列和外部验证队列中）。这些评估指标远优于 TNM 分期系统。
阴茎癌在研究中经常被忽视，缺乏详细的调查重点和指南。本研究首次使用 SEER 数据库的广泛数据以及我们自己机构的数据验证了阴茎癌的预后。我们的发现为外科医生提供了一个重要的工具，以更好地预测阴茎癌的预后，比 TNM 更适合，从而增强了临床决策过程。
