非转移性肾癌根治性肾切除列线图预后模型的构建及验证  

Establishment and validation of a novel nomogram to predict overall survival after radical nephrectomy

作　　者：熊龙滨 邹湘鹏 宁康 罗鑫 彭毓璐 周朝晖 王骏 李震 俞春萍 董培[1] 郭胜杰[1] 韩辉[1] 周芳坚[1] 张志凌[1] Xiong Longbin;Zou Xiangpeng;Ning Kang;Luo Xin;Peng Yulu;Zhou Zhaohui;Wang Jun;Li Zhen;Yu Chunping;Dong Pei;Guo Shengjie;Han Hui;Zhou Fangjian;Zhang Zhiling(Department of Urology,State Key Laboratory of Oncology in South China,Collaborative Innovation Center for Cancer Medicine,Sun Yat-sen University Cancer Center,Guangzhou 510060,China)

机构地区：[1]中山大学肿瘤防治中心、华南恶性肿瘤学国家重点实验室、肿瘤医学协同创新中心泌尿外科,广州510060

出　　处：《中华肿瘤杂志》2023年第8期681-689,共9页Chinese Journal of Oncology

基　　金：国家自然基金(81972382,81872091);广东省杰出青年科学基金(2021B1515020077)。

摘　　要：目的构建一个预测非转移性肾癌根治性肾切除患者术后总生存的列线图模型,并与单纯病理分期和国外常用的Karakiewicz列线图模型和梅奥SSIGN(Stage,Size,Grade,and Necrosis)评分进行比较,最后对患者进行预后分层。方法收集1999—2020年中山大学肿瘤防治中心行根治性肾切除的肾癌患者1246例,采用多因素Cox回归分析筛选预后影响因素,构建预测非转移性肾癌根治性肾切除患者术后总生存的列线图模型,并采用bootstrap抽样进行内部验证,采用时间受试者工作特征(ROC)曲线、校准曲线和临床决策曲线对模型进行评价,采用ROC曲线分析比较该模型与Karakiewicz列线图模型、SSIGN预后评分系统、病理分期的预测效能。根据患者的列线图模型得分进行危险分层。结果多因素Cox回归分析显示,年龄、吸烟史、病理核分级、肉瘤样分化、肿瘤坏死、病理T分期和病理N分期是根治性肾切除术患者总生存的独立影响因素(均P<0.05)。构建预测非转移性肾癌根治性肾切除术患者5、10和15年生存率的中山大学肿瘤防治中心(SYSUCC)列线图模型。bootstrap抽样1000次显示,SYSUCC列线图模型相关因素被纳入多因素Cox回归模型的次数均>800次。SYSUCC列线图模型的C指数为0.770(95%CI:0.716~0.823),高于单纯病理分期[0.674(95%CI:0.621~0.728)]。校准曲线显示,SYSUCC列线图模型预测的生存率与实际生存率相仿。临床决策曲线显示,在一定概率阈值范围内,SYSUCC列线图模型具有净获益。基于857例有详细病理核分级资料的患者的ROC曲线分析显示,SYSUCC列线图模型预测5年和10年总生存的曲线下面积(分别为0.823和0.804)均高于Karakiewicz列线图模型、SSIGN预后评分系统和病理分期(均P<0.05),预测15年总生存的曲线下面积(分别为0.820)高于SSIGN预后评分系统(P<0.05),与Karakiewicz列线图模型和病理分期差异无统计学意义(P>0.05)。通过SYSUCC列线图模�Objective To establish a nomogram prognostic model for predicting the 5-,10-,and 15-year overall survival(OS)of non-metastatic renal cell carcinoma patients managed with radical nephrectomy(RN),compare the modelled results with the results of pure pathologic staging,the Karakiewicz nomogram and the Mayo Clinic Stage,Size,Grade,and Necrosis(SSIGN)score commonly used in foreign countries,and stratify the patients into different prognostic risk subgroups.Methods A total of 1246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center(SYSUCC)from 1999 to 2020 were retrospectively analyzed.Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment,and the bootstrap random sampling was used for internal validation.The time-receiver operating characteristic curve(ROC),the calibration curve and the clinical decision curve analysis(DCA)were applied to evaluate the nomogram.The prediction efficacy of the nomogram and that of the pure pathologic staging,the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve(AUC).Finally,patients were stratified into different risk subgroups according to our nomogram scores.Results A total of 1246 patients managed with RN were enrolled in this study.Multivariate Cox regression analysis showed that age,smoking history,pathological nuclear grade,sarcomatoid differentiation,tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients(all P<0.05).A nomogram model named SYSUCC based on these factors was built to predict the 5-,10-,and 15-year survival rate of the participating patients.In the bootstrap random sampling with 1000 iterations,all these factors occurred for more than 800 times as independent predictors.The Harrell′s concordance index(C-index)of SYSUCC was higher compared with pure pathological staging[0.770(95%CI:0.716-0.823)vs 0.674(95%CI:0.621-0.728)].The calibration curve showed that the survival r

关 键 词：肾肿瘤 根治性肾切除术 预后 列线图 

分 类 号：R737.11[医药卫生—肿瘤]