Chen Tao, Shi Shuibo, Zheng Ping, Zhan Xiangpeng, Zhang Ji, Li Yihe, Li Dongshui, Fu Bin, Chen Luyao
Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang City, China.
Department of Urology, Shangrao Municipal Hospital, Shangrao City, China.
Front Surg. 2023 Jan 13;9:1037203. doi: 10.3389/fsurg.2022.1037203. eCollection 2022.
Metastatic bladder cancer (MBC) is an incurable malignancy, which is prone to early death. We aimed to establish models to evaluating the risk of early death in patients with metastatic bladder cancer.
The data of 1,264 patients with MBC registered from 2010 to 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. We utilized X-tile software to determine the optimal cut-off points of age and tumor size in diagnosis. Univariate and multivariate logistic regression analyses were used to identify significant independent risk factors for total early death and cancer-specific early death, then we construct two practical nomograms. In order to validate our prediction models, we performed calibration plots, receiver operating characteristics (ROCs) curves, decision curve analysis (DCA) and clinical impact curve (CIC).
A total of 1,216 patients with MBC were included in this study. 463 patients died prematurely (≤3 months), and among them 424 patients died of cancer-specific early death. The nomogram of total premature death was created by surgery, chemotherapy, tumor size, histological type, liver metastases, and nomogram of cancer-specific early death was based on surgery, race, tumor size, histological type, chemotherapy, and metastases (liver, brain). Through the verify of calibration plots, receiver operating characteristics (ROCs) curves, decision curve analysis (DCA) and clinical impact curve (CIC), we concluded that nomogram were a valid tool with excellent clinical utility to help clinicians predict premature death in MBC patients.
The nomograms derived from the analysis of patients with MBC, which can provide refined prediction of premature death and furnish clinicians with useful ideas for patient-specific treatment options and follow-up scheduling.
转移性膀胱癌（MBC）是一种无法治愈的恶性肿瘤，容易导致早期死亡。我们旨在建立评估转移性膀胱癌患者早期死亡风险的模型。
从监测、流行病学和最终结果（SEER）数据库中获取2010年至2015年登记的1264例MBC患者的数据。我们使用X-tile软件确定诊断时年龄和肿瘤大小的最佳截断点。采用单因素和多因素逻辑回归分析来确定全因早期死亡和癌症特异性早期死亡的显著独立危险因素，然后构建两个实用的列线图。为了验证我们的预测模型，我们进行了校准图、受试者工作特征（ROC）曲线、决策曲线分析（DCA）和临床影响曲线（CIC）。
本研究共纳入1216例MBC患者。463例患者过早死亡（≤3个月），其中424例死于癌症特异性早期死亡。全因过早死亡列线图由手术、化疗、肿瘤大小、组织学类型、肝转移构建，癌症特异性早期死亡列线图基于手术、种族、肿瘤大小、组织学类型、化疗和转移（肝、脑）。通过校准图、受试者工作特征（ROC）曲线、决策曲线分析（DCA）和临床影响曲线（CIC）的验证，我们得出结论，列线图是一种有效的工具，具有出色的临床实用性，可帮助临床医生预测MBC患者的过早死亡。
从MBC患者分析得出的列线图，可提供对过早死亡的精确预测，并为临床医生提供针对患者的治疗选择和随访安排的有用思路。
