Gao R Q, Li K, Sun J H, Ma Y H, Xu X Y, Xie Y W, Cao J Y
Department of Hepatobiliary and Pancreatic Surgery, the Affiliated Hospital of Qingdao University,Qingdao 266000,China.
Department of Cosmetic Surgery,the Affiliated Hospital of Qingdao University,Qingdao 266000,China.
Zhonghua Wai Ke Za Zhi. 2023 Jan 1;61(1):41-47. doi: 10.3760/cma.j.cn112139-20220713-00311.
To establish and validate a nomogram model for predicting the risk of microvascular invasion(MVI) in hepatocellular carcinoma. The clinical data of 210 patients with hepatocellular carcinoma who underwent hepatectomy at Department of Hepatobiliary and Pancreatic Surgery,the Affiliated Hospital of Qingdao University from January 2013 to October 2021 were retrospectively analyzed. There were 169 males and 41 females, aged((IQR)) 57(12)years(range:30 to 80 years). The patients were divided into model group(the first 170 cases) and validation group(the last 40 cases) according to visit time. Based on the clinical data of the model group,rank-sum test and multivariate Logistic regression analysis were used to screen out the independent related factors of MVI. R software was used to establish a nomogram model to predict the preoperative MVI risk of hepatocellular carcinoma,and the validation group data were used for external validation. Based on the modeling group data,the receiver operating characteristic curve was used to determine that cut-off value of DeRitis ratio,γ-glutamyltransferase(GGT) concentration,the inverse number of activated peripheral blood T cell ratio (-aPBTLR) and the maximum tumor diameter for predicting MVI, which was 0.95((area under curve, AUC)=0.634, 95%: 0.549 to 0.719), 38.2 U/L(AUC=0.604, 95%: 0.518 to 0.689),-6.05%(AUC=0.660, 95%: 0.578 to 0.742),4 cm(AUC=0.618, 95%: 0.533 to 0.703), respectively. Univariate and multivariate Logistic regression analysis showed that DeRitis≥0.95,GGT concentration ≥38.2 U/L,-aPBTLR>-6.05% and the maximum tumor diameter ≥4 cm were independent related factors for MVI in hepatocellular carcinoma patients(all <0.05). The nomogram prediction model based on the above four factors established by R software has good prediction efficiency. The C-index was 0.758 and 0.751 in the model group and the validation group,respectively. Decision curve analysis and clinical impact curve showed that the nomogram model had good clinical benefits. DeRitis ratio,serum GGT concentration,-aPBTLR and the maximum tumor diameter are valuable factors for preoperative prediction of hepatocellular carcinoma with MVI. A relatively reliable nomogram prediction model could be established on them.
建立并验证用于预测肝细胞癌微血管侵犯（MVI）风险的列线图模型。回顾性分析2013年1月至2021年10月在青岛大学附属医院肝胆胰外科接受肝切除术的210例肝细胞癌患者的临床资料。其中男性169例，女性41例，年龄（四分位间距）57（12）岁（范围：30至80岁）。根据就诊时间将患者分为模型组（前170例）和验证组（后40例）。基于模型组的临床资料，采用秩和检验和多因素Logistic回归分析筛选出MVI的独立相关因素。使用R软件建立预测肝细胞癌术前MVI风险的列线图模型，并将验证组数据用于外部验证。基于建模组数据，采用受试者工作特征曲线确定预测MVI的DeRitis比值、γ-谷氨酰转移酶（GGT）浓度、活化外周血T细胞比值倒数（-aPBTLR）和最大肿瘤直径的截断值，分别为0.95（曲线下面积，AUC=0.634，95%：0.549至0.719）、38.2 U/L（AUC=0.604，95%：0.518至0.689）、-6.05%（AUC=0.660，95%：0.578至0.742）、4 cm（AUC=0.618，95%：0.533至0.703）。单因素和多因素Logistic回归分析显示，DeRitis≥0.95、GGT浓度≥38.2 U/L、-aPBTLR>-6.05%和最大肿瘤直径≥4 cm是肝细胞癌患者MVI的独立相关因素（均P<0.05）。R软件基于上述四个因素建立的列线图预测模型具有良好的预测效能。模型组和验证组的C指数分别为0.758和0.751。决策曲线分析和临床影响曲线显示列线图模型具有良好的临床效益。DeRitis比值、血清GGT浓度、-aPBTLR和最大肿瘤直径是术前预测肝细胞癌伴MVI的有价值因素。基于这些因素可建立相对可靠的列线图预测模型。
