肾细胞癌患者术后无进展生存期预测模型的建立  

Establishment of a prediction model for postoperative progression-free survival in patients with renal cell carcinoma

作　　者：李华锋 王振龙[2] 张鸿毅[1] 彭子赫 王晨月 董曜 周海彬 LI Huafeng;WANG Zhenlong;ZHANG Hongyi;PENG Zihe;WANG Chenyue;DONG Yao;ZHOU Haibin(Department of Urology,The First Affiliated Hospital of Xi'an Medical University,Xi'an 710077;Department of Urology,The Second Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710004,China)

机构地区：[1]西安医学院第一附属医院泌尿外科,陕西西安710077 [2]西安交通大学第二附属医院泌尿外科,陕西西安710004

出　　处：《现代泌尿外科杂志》2024年第10期892-897,共6页Journal of Modern Urology

摘　　要：目的分析影响肾细胞癌(RCC)患者术后无进展生存期(PFS)的因素,构建预测RCC患者术后进展风险的列线图模型,并与现有预测模型进行比较。方法回顾性分析2014年4月—2021年11月于西安交通大学第二附属医院泌尿外科进行手术治疗的263例RCC患者的一般及临床资料。根据患者术后是否出现肿瘤进展分为进展组(n=34)和未进展组(n=229)。分析两组患者的临床资料,筛选出与RCC术后PFS相关的预后变量,并据此构建预测RCC患者术后进展风险的列线图模型。比较本模型与加州大学洛杉矶分校综合分期系统(UISS)评分,肿瘤分期、肿瘤大小、肿瘤病理分级以及肿瘤坏死的评分系统(SSIGN评分)和Leibovich评分的受试者工作特征(ROC)曲线下面积(AUC)。列线图校正曲线验证本模型的性能,K折交叉验证评估其外部适用性。结果多因素Cox回归分析结果表明年龄(HR=2.255,95%CI:1.032~4.926)、T分期(HR=5.766,95%CI:2.351~14.142)、病理分级(HR=3.100,95%CI:1.445~6.651)和病理坏死(HR=2.656,95%CI:1.253~5.629)是RCC患者术后肿瘤进展的独立危险因素(P<0.05)。基于以上4个独立预后变量建立RCC患者术后进展风险的列线图预测模型,其1、3、5年的AUC(95%CI)分别为0.750(0.630~0.870)、0.803(0.705~0.902)、0.847(0.757~0.937),预测区分度高于UISS评分、SSIGN评分和Leibovich评分。列线图模型校正曲线显示其预测概率和实际概率的一致性良好。K折交叉验证中本模型1、3、5年的平均AUC分别为0.761、0.808、0.842,表明本模型具备良好的外部适用性。结论基于年龄、T分期、病理分级和病理坏死建立的列线图模型可较为准确地预测RCC患者术后1、3、5年的肿瘤进展风险,有助于临床医生早期识别进展高风险的RCC患者。Objective To analyze factors influencing the postoperative progression-free survival(PFS)in patients with renal cell carcinoma(RCC),construct a nomogram model for predicting PFS,and compare it with other predictive models.Methods A retrospective analysis was conducted on the general and clinical data of 263 RCC patients who underwent surgery at the Department of Urology,the Second Affiliated Hospital of Xi an Jiaotong University,during Apr.2014 and Nov.2021.Patients were divided into the progression group(n=34)and non-progression group(n=229).The data of the two groups were analyzed to identify prognostic variables associated with PFS,and a nomogram model was constructed.The performance of this model was compared with that of the University of California,Los Angeles Integrated Staging System(UISS)score,tumor staging,tumor size,tumor pathological grade,and tumor necrosis scoring system(SSIGN score),and Leibovich score by plotting receiver operating characteristic(ROC)curve and calculating the area under the curve(AUC).Calibration curve of the nomogram was used to validate the model s performance,and K-fold cross-validation was employed to assess its external validity.Results Multivariate Cox regression analysis revealed that age(HR=2.255,95%CI:1.032-4.926),T stage(HR=5.766,95%CI:2.351-14.142),pathological grade(HR=3.100,95%CI:1.445-6.651),and pathological necrosis(HR=2.656,95%CI:1.253-5.629)were independent risk factors of PFS(P<0.05).The nomogram model based on these four independent variables had AUCs(95%CI)of 0.750(0.630-0.870),0.803(0.705-0.902),and 0.847(0.757-0.937)for 1,3,and 5 years,respectively,which were higher than those of UISS score,SSIGN score,and Leibovich score.The calibration curve of the nomogram showed good consistency between predicted and actual probabilities.In K-fold cross-validation,the average AUCs of the nomogram at 1,3,and 5 years were 0.761,0.808,and 0.842,indicating good external validity of the nomogram.Conclusion The nomogram based on age,T stage,pathological grade and pathological n

关 键 词：肾细胞癌 列线图 预测模型 无进展生存期 加州大学洛杉矶分校综合分期系统 肿瘤分期、肿瘤大小、肿瘤病理分级以及肿瘤坏死的评分系统 Leibovich评分 

分 类 号：R737.11[医药卫生—肿瘤]