Annals of Hepatology (Nov 2020)

Preoperative evaluation and prediction of clinical scores for hepatocellular carcinoma microvascular invasion: a single-center retrospective analysis

  • Yong Zhu He,
  • Kun He,
  • Rui Qin Huang,
  • Ze Liang Wang,
  • Shao Wei Ye,
  • Li Wen Liu,
  • Qi Jie Luo,
  • Ze Min Hu

Journal volume & issue
Vol. 19, no. 6
pp. 654 – 661

Abstract

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Introduction: Microvascular invasion (MVI) of is generally considered to be an important prognostic factor for hepatocellular carcinoma (HCC) after operation, An accurate prediction of MVI before operation is helpful for clinical decision-making before operation. Material and methods: A retrospective analysis of 227 cases of hepatocellular carcinoma patients after hepatectomy has been confirmed the pathological result whether there was MVI, and has been determined the independent risk factors of MVI. Based on these independent risk factors, we constructed a clinical scoring risk model for predicting MVI. Results: Among the 227 patients with HCC, 74 (34.6%) were MVI positive. Using receiver operating characteristic (ROC) curve and logistic regression model, we found that alpha-fetoprotein(AFP)≥158 ng/mL(odds ratio[OR] = 4.152,95% confidence interval [95%CI]:1.602∼10.760,p = 0.003), Des-γ-carboxy prothrombin (DCP)≥178mAU/mL(OR = 9.730,95%CI:3.392∼27.910,p < 0.001), circulating tumor cells (CTCs)≥3/3.2 ml(OR = 7.747,95%CI:3.019∼19.881,P < 0.001), maximum tumor diameter≥59 mm(OR = 3.467,95%CI:1.368∼8.669,p = 0.008) and tumor margin unsmoothness(OR = 0.235,95%CI:0.096∼0.573,p = 0.001) were independent risk factors for MVI, they predicted that the area under the curve of MVI was 0.752, 0.777, 0.857, 0.743 and 0.333, respectively. Based on these five independent risk factors, we constructed a clinical scoring risk model for predicting MVI. The model predicts that the area under the curve of MVI is 0.922, and its prevalence rate from 0 to 5 are 3.1%(1/32), 5.3%(4/76), 12.2%(5/41), 66.7%(20/30), 87.9%(29/33), 100%(15/15), respectively (P < 0.001). Conclusion: Based on AFP, DCP, CTC, maximum tumor diameter and tumor margin unsmoothness, we constructed a model to predict the risk of MVI clinical score, so as to make a more accurate individualized treatment plan before operation, which has important clinical significance and application prospect to improve the curative effect of HCC.

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