Wang Shun-De, Ge Cheng-Guo, Zhang Jun-Yong
Department of Urology, The ChenJiaqiao Hospital of ShaPingba District of Chongqing City, Chongqing, China.
Department of Urology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Transl Cancer Res. 2022 Aug;11(8):2742-2756. doi: 10.21037/tcr-22-46.
The aim of this study was to investigate the incidence, epidemiologic characteristics, prognostic factors and survival of patients with bladder cancer.
Bladder cancer patients diagnosed between 2010 and 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox proportional hazards regression analyses were used to identify the independent prognostic factors for overall survival. Kaplan-Meier survival analysis and nomogram analysis were constructed based on the identified independent prognostic factors.
A total of 95,329 eligible bladder cancer patients were included in this study. Eight independent risk factors, including age, histologic type, race, tumor, node and metastasis (TNM) stage, American Joint Committee on Cancer (AJCC) stage, surgery, tumor metastasis and summary stage, were recognized by using multivariate logistic regression models. By comprising these factors, a predictive nomogram was constructed to predict the 1-, 3-, and 5-year overall survival possibilities. The concordance index and calibration curve showed that the nomogram had robust and accurate performance.
Bladder cancer is the most common cancer of the urinary system, but the overall incidence has been decreasing yearly since 1992. Our results demonstrate eight factors significantly associated with overall survival in bladder cancer patients. Based on these factors, we established and validated a nomogram, which has the potential to provide an individualized prediction of overall survival in patients with bladder cancer.
本研究旨在调查膀胱癌患者的发病率、流行病学特征、预后因素及生存率。
从监测、流行病学和最终结果(SEER)数据库中识别出2010年至2015年期间诊断的膀胱癌患者。采用单因素和多因素Cox比例风险回归分析来确定总生存的独立预后因素。基于所确定的独立预后因素构建Kaplan-Meier生存分析和列线图分析。
本研究共纳入95329例符合条件的膀胱癌患者。通过多因素逻辑回归模型识别出八个独立危险因素,包括年龄、组织学类型、种族、肿瘤、淋巴结和转移(TNM)分期、美国癌症联合委员会(AJCC)分期、手术、肿瘤转移和总结分期。通过纳入这些因素,构建了一个预测列线图以预测1年、3年和5年总生存可能性。一致性指数和校准曲线表明该列线图具有稳健且准确的性能。
膀胱癌是泌尿系统最常见的癌症,但自1992年以来总体发病率逐年下降。我们的结果表明八个因素与膀胱癌患者的总生存显著相关。基于这些因素,我们建立并验证了一个列线图,其有可能为膀胱癌患者的总生存提供个性化预测。