检验医学 ›› 2020, Vol. 35 ›› Issue (8): 741-748.DOI: 10.3969/j.issn.1673-8640.2020.08.001

• •    下一篇

基于临床常用检验项目的原发性肝细胞肝癌术前微血管侵犯诊断模型研究

童林, 黄晨军, 高致远, 周军, 房萌, 肖潇, 何羽童, 洪松, 许敏凡, 朱飞飞, 高春芳()   

  1. 上海东方肝胆外科医院实验诊断科,上海 200438
  • 收稿日期:2019-03-18 出版日期:2020-08-30 发布日期:2020-09-24
  • 作者简介:作者简介:童 林,男,1986年生,学士,主管技师,主要从事原发性肝癌的鉴别诊断及分层管理模型的建立及应用研究。 黄晨军,男,1994年生,硕士,主要从事肝脏肿瘤相关标志物的研究。 童林与黄晨军对本研究具有同等贡献,并列为第一作者。
  • 基金资助:
    国家科技重大专项(2018ZX10302205-003);上海市分子肿瘤创新集群项目(2019CXJQ03);上海市科学技术委员会重点项目(17JC1404500);上海市科学技术委员会西医引导项目(17411960500)

Study on the judgment model of preoperative microvascular invasion in HCC based on common clinical determination items

TONG Lin, HUANG Chenjun, GAO Zhiyuan, ZHOU Jun, FANG Meng, XIAO Xiao, HE Yutong, HONG Song, XU Minfan, ZHU Feifei, GAO Chunfang()   

  1. Department of Laboratory Diagnosis,Shanghai Eastern Hepatobiliary Surgery Hospital,Shanghai 200438,China
  • Received:2019-03-18 Online:2020-08-30 Published:2020-09-24

摘要:

目的 建立基于临床常用检验项目的原发性肝细胞肝癌(HCC)微血管侵犯(MVI)诊断模型。方法 以5 602例HCC患者作为训练组,以另外1 905例HCC患者作为验证组,收集所有患者的临床资料,包括性别、年龄、肿瘤个数、肿瘤大小、Edmondson分级、MVI发生情况及术前48项指标的检测结果。在训练组中,采用Logistic回归分析评估HCC患者术前发生MVI的危险因素,依此建立联合诊断模型,并在验证组中进行独立验证。采用受试者工作特征(ROC)曲线评估联合诊断模型PA-SALAD诊断HCC患者术前发生MVI的效能。结果 训练组与验证组之间年龄、白蛋白(Alb)、丙氨酸氨基转移酶(ALT)、天门冬氨酸氨基转移酶(AST)、γ-谷氨酰基转移酶(GGT)、碱性磷酸酶(ALP)、α-L-岩藻糖苷酶(AFU)、唾液酸(SA)、凝血酶原时间(PT)、肿瘤个数、肿瘤大小、MVI比例差异均有统计学意义(P<0.05),其他项目2个组之间差异均无统计学意义(P>0.05)。Logistic回归分析结果显示,年龄、血小板(PLT)、Alb、SA、甲胎蛋白(AFP)、异常凝血酶原(DCP)、甲胎蛋白异质体(AFP-L3)是MVI发生的危险因素[比值比(OR)分别为0.981、0.998、0.971、1.016、1.226、1.361、1.012]。根据Logistic回归分析结果建立的联合诊断模型为PA-SALAD=0.220-0.002×PLT-0.019×年龄+0.016×SA-0.029×Alb+0.012×AFP-L3+0.204×lgAFP+0.308×lgDCP。ROC曲线分析结果显示,在训练组中,PA-SALAD模型诊断有MVI的曲线下面积(AUC)为0.695,最佳临界值为-0.235 3,敏感性为69.3%,特异性为60.4%;在验证组中,PA-SALAD模型诊断有MVI的AUC为0.704,以训练组的最佳临界值-0.235 3作为临界值,敏感性为66.5%,特异性为62.0%。结论 基于临床常用检验项目的联合诊断模型PA-SALAD诊断HCC患者是否发生MVI,特别是高危MVI有一定的价值。

关键词: 原发性肝细胞肝癌, 微血管侵犯, Logistic回归分析

Abstract:

Objective To establish a judgment model of microvascular invasion(MVI) in hepatocellular carcinoma(HCC) based on common clinical determination items. Methods A total of 5 602 patients with HCC were enrolled as training group,and 1 905 patients with HCC were enrolled as validation group. The clinical data,including sex,age,tumor number,tumor size,Edmondson grade,MVI occurrence and preoperative 48 indexes,were collected. In training group, Logistic regression analysis was used to evaluate the risk factors of MVI in patients with HCC before operation,a judgment model was established,and independent validation was performed in validation group. Receiver operating characteristic(ROC) curve was used to evaluate the performance of the judgment model,PA-SALAD,for the diagnosis of MVI occurrence in preoperative HCC patients. Results There was statistical significance in age,albumin(Alb),alanine aminotransferase(ALT),aspartate aminotransferase(AST),gamma-glutamyltransferase(GGT),alkaline phosphatase(ALP),alpha-L-fucosidase(AFU),sialic acid(SA),prothrombin time(PT),tumor number,tumor size and MVI ratio between training and validation groups(P<0.05). There was no statistical significance for the other indexes between the 2 groups(P>0.05). Logistic regression analysis showed that age,platelet(PLT),Alb,SA,alpha-fetoprotein(AFP),des-gamma-carboxy prothrombin(DCP) and alpha-fetoprotein heterogeneity(AFP-L3) were risk factors for MVI occurrence [odds ratios(OR) were 0.981,0.998,0.971,1.016,1.226,1.361 and 1.012]. Based on the results of Logistic regression analysis,the judgment model,PA-SALAD=0.220-0.002×PLT-0.019×age+0.016×SA-0.029×Alb+0.012×AFP-L3+0.204×lgAFP+0.308×lgDCP,was established. ROC curve analysis showed that the area under curve(AUC),sensitivity and specificity of PA-SALAD for discriminating MVI in training group were 0.695,69.3% and 60.4%,and the optimal cut-off value was -0.235 3. In validation group,the AUC,sensitivity and specificity were 0.704,66.5% and 62.0%,and the optimal cut-off value was -0.235 3. Conclusions The judgment model,PA-SALAD,based on common clinical determination items is of certain value to determine whether MVI occurs in HCC patients,especially for patients at high risk of MVI.

Key words: Hepatocellular carcinoma, Microvascular invasion, Logistic regression model

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