天津医药

天津医药 ›› 2022, Vol. 50 ›› Issue (5): 523-527.doi: 10.11958/20212723

• 应用研究 • 上一篇    下一篇

肝细胞癌微血管侵犯相关危险因素分析及预测模型的构建#br#

谭玉莹1，张炜琪1，谢炎2，李江2，李俊杰2，蒋文涛2△   

  1. 1天津医科大学一中心临床学院（邮编300192）；2天津市第一中心医院肝移植科
  • 收稿日期:2021-12-09 修回日期:2022-01-13 出版日期:2022-05-15 发布日期:2022-07-04
  • 基金资助:
    国家自然科学基金面上项目（81870444）；天津市自然科学基金（19JCQNJC10300）；天津市卫生健康委员会基金（ZC20100）

The risk factor analysis and predictive model construction of microvascular invasion in hepatocellular carcinoma

TAN Yuying1, ZHANG Weiqi1, XIE Yan2, LI Jiang2, LI Junjie2, JIANG Wentao2△   

  1. 1 The First Central Clinical School, Tianjin Medical University, Tianjin 300192, China; 2 Department of Liver Transplantation, Tianjin First Central Hospital
  • Received:2021-12-09 Revised:2022-01-13 Published:2022-05-15 Online:2022-07-04

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摘要： 目的　探究肝细胞癌微血管侵犯（MVI）的相关危险因素，并构建MVI的预测模型。方法　分析首次行原位肝移植的178例肝细胞癌患者的临床资料并根据术后病理结果分为MVI阳性组（76例）及MVI阴性组（102例）。收集患者术前一般资料、术前CT或MRI检查结果、术前实验室检查结果、病理结果，并对患者进行随访，记录所有患者的无复发生存时间。通过受试者工作特征（ROC）曲线分析甲胎蛋白（AFP）、天冬氨酸转氨酶/淋巴细胞比值（ALRI）、肿瘤最大直径、γ-谷氨酰转移酶/淋巴细胞计数比值（GLR）和中性粒细胞/淋巴细胞比值（NLR）对于MVI的诊断价值，并确定最佳截断值；多因素Logistic回归分析MVI的独立危险因素，并建立预测评分模型。通过评分模型的最佳截断值将患者分为MVI高危组（3~4分，67例）及MVI低危组（0~2分，111例），绘制Kaplan-Meier生存曲线，比较2组的无复发生存率。结果　与MVI阴性组相比，MVI阳性组患者中多个肿瘤、肿瘤最大直径＞3.75 cm、术前AFP＞53.8 μg/L、NLR＞3、GLR＞85.84以及ALRI＞75.36比例较高（P＜0.05）。肿瘤最大直径＞3.75 cm、术前AFP＞53.8 μg/L、GLR＞85.84、ALRI＞75.36是肝细胞癌患者MVI的独立危险因素（P＜0.05），由上述危险因素构成的评分系统拟合优度良好（χ2=2.553，P=0.862），曲线下面积=0.787，P＜0.01，最佳截断值为2，特异度为0.814，敏感度为0.632。生存分析结果显示，MVI低危组患者术后无复发生存率明显高于高危组患者（Log-rank χ2=37.584，P＜0.01）。结论　术前GLR、ALRI、AFP及肿瘤最大直径是MVI的独立危险因素，由其组成的预测模型对于术前MVI及术后复发情况具有一定的预测价值。

关键词: 肝肿瘤, γ-谷氨酰转移酶, 天冬氨酸转氨酶类, 肝移植, 淋巴细胞计数, 微血管侵犯, 预测模型

Abstract: Objective　To explore the related risk factors of microvascular invasion (MVI) in hepatocellular carcinoma (HCC), and to construct a predictive model of MVI. Methods　The clinical data of 178 patients with HCC who underwent orthotopic liver transplantation for the first time were analyzed. Patients were divided into the MVI positive group (76 cases) and the MVI negative group (102 cases) according to postoperative pathological results. The preoperative general information, preoperative CT or MRI examination results, preoperative laboratory examination results, and pathological results of the patients were collected, and the patients were followed up. The recurrence-free survival (RFS) time was recorded for all patients. The diagnostic values of alpha-fetoprotein (AFP), aspartate aminotransferase to lymphocyte ratio (ALRI), tumor maximum diameter, γ-glutamyl transpeptidase to lymphocyte count ratio (GLR) and neutrophil to lymphocyte ratio (NLR) were analyzed through receiver operating characteristic (ROC) curve for the diagnosis of MVI, and the optimal cut-off value was determined. Multivariate Logistic regression was used to analyze the independent risk factors of MVI, and a predictive scoring model was established. The patients were divided into the MVI high-risk group (3-4 points, 67 cases) and the MVI low-risk group (0-2 points, 111 cases) according to the optimal cut-off value of the scoring model. The Kaplan-Meier survival curve was drawn to compare the RFS rate of the two groups. Results　Compared with the MVI-negative group, there were higher proportions of multiple tumors, tumor maximum diameter＞3.75 cm, preoperative AFP＞53.8 μg/L, NLR＞3, GLR＞85.84 and ALRI＞75.36 in the MVI-positive group (P＜0.05). The largest tumor diameter＞3.75 cm, preoperative AFP＞53.8 μg/L, GLR＞85.84, ALRI＞75.36 were independent risk factors for MVI in patients with hepatocellular carcinoma (P＜0.05). The scoring system composed of the above risk factors had good goodness of fit (χ2=2.553, P=0.862), area under the curve=0.787, P＜0.01, the optimal cut-off value was 2, the specificity was 0.814, and the sensitivity was 0.632. The results of survival analysis showed that the RFS rate of patients was significantly higher in the MVI low-risk group than that of patients in the MVI high-risk group (Log-rank χ2=37.584, P＜0.01). Conclusion　Preoperative GLR, ALRI, AFP and maximum tumor diameter are independent risk factors for MVI, and the predictive model composed of them has certain predictive value for the presence of MVI before surgery and postoperative recurrence.

Key words: liver neoplasms, gamma-glutamyltransferase, aspartate aminotransferases, liver transplantation, lymphocyte count, microvascular invasion, predictive model

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