原发性肝细胞癌伴微血管侵犯术前早期诊断列线图预测模型的建立与验证  

Establishment and validation of a nomogram prediction model for early preoperative diagnosis of hepatocellular carcinoma with microvascular invasion

作　　者：张宇波 牛一鸣 赵鹏[1] 郝继 雷鹏[2] 刘迪[2] Zhang Yubo;Niu Yiming;Zhao Peng;Hao Ji;Lei Peng;Liu Di(Graduate School of Ningxia Medical University,Yinchuan 750004,China;Department of Hepatobiliary Surgery,General Hospital of Ningxia Medical University,Yinchuan 750004,China)

机构地区：[1]宁夏医科大学研究生院,银川750004 [2]宁夏医科大学总医院肝胆外科,银川750004

出　　处：《中华肝胆外科杂志》2021年第10期721-726,共6页Chinese Journal of Hepatobiliary Surgery

基　　金：宁夏重点研发计划项目(2018BEG03001)。

摘　　要：目的建立一项更易于临床操作、推广的关于原发性肝细胞癌伴微血管侵犯(MVI)术前早期诊断列线图预测模型,通过内部验证及外部验证对模型进行评估。方法回顾性分析2017年1月至2020年12月期间宁夏医科大学总医院收治的294例肝细胞癌患者的临床资料。依据就诊时间分为两组:建模组(n=231)和验证组(n=63)。根据既往文献和相关临床经验且易于术前获取的原则,初步选取γ-谷氨酰基转移酶(GGT)、血小板计数/淋巴细胞计数比值(PLR)、纤维蛋白原/白蛋白比值(FAR)、淋巴细胞计数/单核细胞计数比值(LMR)、天门冬氨酸氨基转移酶/血小板计数比值(APRI)等指标进行考察,筛选确定肝细胞癌伴MVI的独立危险因素,并以此构建列线图预测模型,将验证组应用于模型进行外部验证。结果本研究共纳入294例患者,其中男性223例,女性71例,年龄(55.1±10.9)岁。建模组中MVI阳性95例,MVI阴性136例;验证组中MVI阳性38例,MVI阴性25例。多因素logistic回归分析结果显示,FAR>0.06、GGT>50 U/L、APRI>0.16、肿瘤长径>5 cm、LMR>3.57和PLR>98.75是肝细胞癌发生MVI的独立危险因素(P<0.05)。以此构建的列线图模型的实际预测结果与理想结果相接近,具有良好的预测性能,C指数均在0.71~0.90之间。运用决策曲线分析评估预测模型肝细胞癌术前MVI风险的临床净获益情况,结果显示,当净获益率>0时,预测模型阈值为4%~77%,表明该模型具有良好的临床应用价值。结论根据术前临床指标GGT、APRI、LMR、PLR、FAR及肿瘤长径构建列线图模型,可以简单、准确地对原发性肝癌伴MVI进行预测。Objective To establish a convenient preoperative nomogram prediction model for early diagnosis of hepatocellular carcinoma(HCC)with microvascular invasion(MVI),and to evaluate the model through internal and external validations for use informulating reasonable and individualized treatment strategies for patients with early-staged HCC.Methods The clinical data of 294 patients who underwent hepatectomy at the General Hospital of Ningxia Medical University from January 2017 to December 2020 were retrospectively collected and analyzed.Based on the different admission times,they were divided into the training group(n=231)and the validation group(n=63).Based on the results from previous published literatures and our relevant clinical experience,risk factors including γ-glutamyltranspeptidase(GGT),platelet-lymphocyte ratio(PLR),fibrinogen albumin ratio(FAR),lymphocyte monocyte count ratio(LMR)and ALT-platelet ratio(APRI)were subjected to multi-factor logistic regression analysis to determine independent risk factors of HCC with MVI,and a nomogram prediction model was then constructed.The validation group was applied to the model for validation.Results Of 294 patients who were enrolled in this study,there were 231 patients in the training cohort,with an average age of(55.1±10.9)years.In the training group,95 patients were MVI positive and 136 patients were MVI negative.In the validation group,38 patients were MVI positive and 25 patients were MVI negative.Logistic regression analysis showed that FAR>0.06,GGT>50 U/L,APRI>0.16,tumor diameter>5 cm,LMR>3.57 and PLR>98.75 were independent risk factors(P<0.05),and a nomogram prediction model was established.The correction curve of the nomogram showed that the actual prediction result was close to the ideal result of the prediction model.The internal validated results showed the C-indexes to be between 0.71 and 0.90,and the prediction model had good discrimination.DCA curve was used to evaluate the clinical net benefit of the predictive model.When the net benefit rate was abo

关 键 词：癌 肝细胞 微血管 列线图 预测模型 

分 类 号：R735.7[医药卫生—肿瘤]