术前SII联合FAR构建的列线图模型对Child-Pugh A级HCC患者术后生存期的预测价值  

Predictive value of preoperative SII combined a nomogram constructed by FAR for postoperative survival of patients with Child-Pugh class A HCC

作　　者：付相玉 江致贤 严芝强[3] 左石 FU Xiangyu;JIANG Zhixian;YAN Zhiqiang;ZUO Shi(Department of Hepatobiliary Surgery,the Affiliated Hospital of Guizhou Medical University,Guiyang 550004,Guizhou,China;School of Clinical Medicine,Guizhou Medical University,Guiyang 550004,Guizhou,China;Department of Gastrointestinal Surgery,the Affiliated Hospital of Guizhou Medical University,Guiyang 550004,Guizhou,China)

机构地区：[1]贵州医科大学附属医院肝胆外科,贵州贵阳550004 [2]贵州医科大学临床医学院,贵州贵阳550004 [3]贵州医科大学胃肠外科,贵州贵阳550004

出　　处：《贵州医科大学学报》2024年第7期1026-1034,共9页Journal of Guizhou Medical University

基　　金：国家自然科学基金地区项目(82260535)。

摘　　要：目的探讨术前系统免疫炎症指数(SII)、纤维蛋白原和白蛋白比值(FAR)对Child-PughA级肝细胞癌患者术后总生存期(OS)的预测价值。方法收集接受手术治疗的121例肝细胞癌(HCC)患者的SII、FAR、实验室检查数据、临床病理和随访资料,采用受试者工作特征(ROC)曲线分析SII、FAR和其他临床指标的最佳截断值,并对患者进行分组;分析SII、FAR与患者临床病理特征之间的关联,利用单因素和多因素Cox回归分析明确影响HCC患者OS的独立危险因素、并构建列线图预测模型;使用C-指数、校准曲线和时间依赖的ROC曲线评估模型的诊断效能,并通过综合判别改善指数(IDI)、净重新分类指数(NRI)和决策曲线分析法(DCA)对模型预测能力进行评价。结果ROC曲线显示SII的最佳截断值为362.876、患者分为高表达组(>362.876,n=56)和低表达组(≤362.876,n=65),FAR的最佳截断值为0.075、患者分为高表达组(≥0.075,n=69)和低表达组(<0.075,n=52);Kaplan-Meier分析显示,低SII组、低FAR组患者1、3、5年OS优于高SII组、高FAR组(P<0.005);单因素、多因素Cox回归分析结果显示,肿瘤最大直径、红细胞计数(RBC)、纤维蛋白原(Fg)、SII、FAR是影响HCC患者OS的独立危险因素(P<0.05),并构建列线图模型;列线图模型经内部验证后C-指数为0.696(0.551~0.841),预测1、3、5年OS的曲线下面积(AUCs)分别为0.739、0.744、0.776,并且校准曲线、NRI/IDI和DCA曲线提示模型在生存预后的预测上有一定的效能。结论术前SII、FAR与Child-Pugh A级HCC患者的预后相关,高水平SII、FAR患者的预后较差。Objective To investigate the prognostic value of preoperative systemic immune-inflammation index(SII)and fibrinogen-to-albumin-ratio(FAR)for the postoperative overall survival(OS)of patients with Child-Pugh grade A hepatocellular carcinoma(HCC).Methods SII,FAR,laboratory examination data,clinical pathology and follow-up data were collected from 121 patients with HCC who underwent surgery.Receiver operating characteristic(ROC)curve was used to analyze the optimal cutoff values for SII,FAR and other clinical indicators to group the patients.The associations of SII and FAR with clinical pathological characteristics of the patients were analyzed.Univariate and multivariate Cox regression analyses were performed to identify independent risk factors affecting OS of the patients with HCC and construct a nomogram prediction model.The diagnostic performance of the model was evaluated using C-index,calibration curve and time-dependent ROC curve.The predictive ability of the model was assessed through integrated discrimination improvement(IDI),net reclassification index(NRI),and decision curve analysis(DCA).Results ROC curve showed that the optimal cut-off value for SII was 362.876,which was used to divide the patients into a high SII group(>362.876,n=56)and a low SII group(≤362.876,n=65).The best cut-off value for FAR was 0.075,which was used to divided the patients into a high FAR group(≥0.075,n=69)and a low FAR group(<0.075,n=52).Kaplan-Meier analysis showed that the low SII and low FAR groups had significantly better OS than the high SII and high FAR groups did(P<0.005).Univariate and multivariate Cox regression analyses showed that tumor maximum diameter,red blood cell count(RBC),fibrinogen(Fg),SII,and FAR were independent risk factors affecting OS of the patients with HCC(P<0.05).A nomogram was constructed.After internal validation for the nomogram,the C-index was 0.696(0.551–0.841),and the areas under the curve(AUC s)for predicting OS of 1,3,and 5 years were 0.739,0.744 and 0.776,respectively.The calibration cu

关 键 词：肝细胞肿瘤 系统免疫炎症指数 纤维蛋白原/白蛋白比值 列线图 预后 

分 类 号：R735.7[医药卫生—肿瘤]