【摘要】 目的 探讨局限性肾透明细胞癌（ccRCC）患者的预后情况并构建预后模型。方法 对苏州大学附属第一医院十梓街院区泌尿外科2012年10月至2021年7月收治的局限性ccRCC患者的临床和病理资料进行回顾性分析，并通过电话随访登记生存状态。共纳入445例患者，其中男性310例，女性135例。截至2024年12月，398例存活，47例死亡。依据生存状态将患者分为存活组和死亡组，比较两组间临床病理特征的差异。使用Cox多因素分析筛选独立危险因素，并构建预后列线图，通过校准曲线评估模型拟合度。结果 存活组和死亡组在年龄、手术方式、肿瘤直径、Fuhrman分级和T分期方面差异有统计学意义（P<0.05）。Cox多因素分析显示，年龄（HR=1.033,95%CI 1.006～1.061,P=0.018）及Fuhrman分级（HR=7.511,95%CI 3.890～1 4.501,P<0.001）为预后不良的独立危险因素。基于此分析构建的预后列线图及其校准曲线显示模型拟合度良好（χ~2=4.509,P=0.105）。结论 年龄和Fuhrman分级是局限性ccRCC不良预后的独立危险因素，所构建的预后模型具有较高的预测能力。更多还原

【Abstract】 Objective To investigate the prognosis of patients with localized clear cell renal cell carcinoma(ccRCC) and to develop a prognostic model. Methods A retrospective analysis was conducted on the clinical and pathological data of patients with localized ccRCC, who were treated in the Department of Urology at the First Affiliated Hospital of Soochow University Shizi Street Campus, from October 2012 to July 2021. Survival status was collected through telephone follow-ups. A total of 445patients were included, comprising 310 males and 135 females. As of December 2024, 398 patients were alive and 47 had passed away. Patients were divided into survival and deceased groups based on survival status, and clinicopathological characteristics of the two groups were compared. Cox multivariate analysis was performed to identify independent risk factors, and a prognostic nomogram was constructed. Model fit was evaluated using a calibration curve. Results Significant differences were found between the survival and deceased groups in terms of age, surgical method, tumor size, Fuhrman grade, and T stage(P<0.05).Cox multivariate analysis indicated that age(HR=1.033, 95%CI 1.006-1.061, P=0.018) and Fuhrman grade(HR=7.511, 95%CI3.890-14.501, P<0.001) were independent risk factors for poor prognosis. The prognostic nomogram and calibration curve based on this analysis showed good model fit(χ~2=4.509, P=0.105). Conclusion Age and Fuhrman grade are independent risk factors for poor prognosis in patients with localized ccRCC. The constructed prognostic model demonstrates high predictive ability.更多还原