Wu Jie, Shang Bing-Qing, Shou Jian-Zhong, Wang Zong-Ping
Department of Urology, Zhejiang Cancer Hospital, Hangzhou, China.
Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China.
Int J Surg. 2025 Feb 1;111(2):2309-2312. doi: 10.1097/JS9.0000000000002222.
This study aimed to develop a predictive nomogram model and a risk classification system to predict the likelihood of lymph node metastases for non-metastatic muscle-invasive bladder cancer (MIBC) patients using a large population-based cancer database. According to our nomogram, larger tumor size, overlapping lesions, young age, female, poorly differentiated histological grade, and advanced T stage, are independent risk factors for pN+. A precise nomogram model predicting pN+ probability for MIBC patients can support patient risk stratification and outcome estimation, and eventually guide clinical decision-making.
本研究旨在利用一个基于人群的大型癌症数据库，开发一种预测列线图模型和风险分类系统，以预测非转移性肌层浸润性膀胱癌（MIBC）患者发生淋巴结转移的可能性。根据我们的列线图，肿瘤体积较大、存在重叠病变、年龄较小、女性、组织学分级差以及T分期较晚是pN+的独立危险因素。一个精确的预测MIBC患者pN+概率的列线图模型可以支持患者风险分层和预后评估，并最终指导临床决策。
