Yang Libin, Chen Chao, Wang Qianghui, Zhuang Zhiliang, Sun Tao
Department of Urology, Ningbo Municipal Hospital of Traditional Chinese Medicine (TCM), Affiliated Hospital of Zhejiang Chinese Medical University, Ningbo, Zhejiang, China.
Med Sci Monit. 2025 Jan 29;31:e946332. doi: 10.12659/MSM.946332.
BACKGROUND Transitional cell bladder carcinoma (tcBC) is the predominant form of bladder cancer, making up around 95% of reported cases. Prognostic factors for older individuals with tcBC differ from those affecting younger patients. The main purpose of this study was to establish a prognostic competing risk model for elderly patients with tcBC. MATERIAL AND METHODS We conducted a retrospective analysis using data from the SEER database, randomly assigning patients to training and validation groups. We applied proportional subdistribution hazard (SH) to assess risk factors for cancer-related mortality (CSM). A competitive risk model was created to predict cancer-specific survival in elderly patients with tcBC. Model validation involved evaluating the area under the receiver operating curve, the consistency index, and a calibration curve. The Kaplan-Meier (K-M) curve was then used to compare mortality risk between high-risk and low-risk groups identified by the model. RESULTS This study randomly assigned 61 293 patients from the SEER database into training (42 905 patients) and validation (18 388 patients) groups in a 7: 3 ratio. Using a proportional subdistribution hazards model, we identified prognostic risk factors such as age, race, sex, marital status, TNM staging, grade, and metastatic status in brain, bone, liver, and lung. We developed a competitive risk model to predict 5-year cancer-specific survival (CSS) in elderly tcBC patients, achieving consistency index (C-index) values of 0.814 and 0.815 for the training and validation groups, respectively. Kaplan-Meier (K-M) analysis revealed 5-year survival probabilities of 35.1% (high-risk) and 42.2% (low-risk) in the training group, with similar rates of 35.7% and 42.0% in the validation group, both showing statistically significant differences (log-rank P<0.01). CONCLUSIONS We successfully established a competitive risk model for forecasting cancer-specific survival in elderly tcBC patients, primarily relying on these identified risk factors. The validation outcomes indicate the model's accuracy and dependability, making it a highly efficient predictive instrument. This tool enables making personalized clinical decisions for both medical professionals and patients.
背景 移行细胞膀胱癌（tcBC）是膀胱癌的主要形式，约占报告病例的95%。老年tcBC患者的预后因素与影响年轻患者的因素不同。本研究的主要目的是为老年tcBC患者建立一个预后竞争风险模型。
材料与方法 我们使用监测、流行病学和最终结果（SEER）数据库的数据进行回顾性分析，将患者随机分配到训练组和验证组。我们应用比例子分布风险（SH）来评估癌症相关死亡率（CSM）的风险因素。创建了一个竞争风险模型来预测老年tcBC患者的癌症特异性生存。模型验证包括评估受试者工作特征曲线下面积、一致性指数和校准曲线。然后使用Kaplan-Meier（K-M）曲线比较模型确定的高风险组和低风险组之间的死亡风险。
结果 本研究将SEER数据库中的61293例患者以7:3的比例随机分配到训练组（42905例患者）和验证组（18388例患者）。使用比例子分布风险模型，我们确定了年龄、种族、性别、婚姻状况、TNM分期、分级以及脑、骨、肝和肺的转移状态等预后风险因素。我们开发了一个竞争风险模型来预测老年tcBC患者的5年癌症特异性生存（CSS），训练组和验证组的一致性指数（C-index）值分别为0.814和0.815。Kaplan-Meier（K-M）分析显示，训练组的5年生存概率为35.1%（高风险）和42.2%（低风险），验证组的类似率为35.7%和42.0%，两者均显示出统计学显著差异（对数秩P<0.01）。
结论 我们成功建立了一个用于预测老年tcBC患者癌症特异性生存的竞争风险模型，主要依赖于这些确定的风险因素。验证结果表明该模型的准确性和可靠性，使其成为一种高效的预测工具。该工具能够为医疗专业人员和患者做出个性化的临床决策。
