Establishment and Validation of Diagnostic Model of Microvascular Invasion in Hepatocellular Carcinoma

Abstract

Abstract Background: Microvascular invasion (MVI) is closely related to high recurrence and poor prognosis in patients with hepatocellular carcinoma (HCC). We aimed to establish a preoperative diagnostic model of MVI for HCC based on the clinical characteristics and serum detectors of HCC patients. Methods: In total, 1027 hepatocellular carcinoma patients hospitalized at Shandong Provincial Hospital from January 2016 to August 2021 were included and randomly divided into the development group and validation group at a ratio of 3:1. Independent sample t test, Mann-Whitney U test, Chi-square test and Fisher exact test were applied to assess the difference of clinical characteristics and serum index results of the two cohorts. Univariate and multivariate logistic regression analyses were carried out to screen the independent risk factors of HCC patients with microvascular invasion. By using these independent risk factors, a preoperative diagnostic nomogram of HCC for MVI was established and verified. The receiver operating characteristic (ROC) curves, calibration curves and decision curve analyses (DCA) were used to estimate the discrimination and clinical application of the nomogram. In addition, the value of this diagnosticmodel in diagnosing microvascular invasion in different stages of hepatocellular carcinoma was further discussed. Results: Through univariate and multivariate analyses, independent riskfactors for MVI of HCCinvolved Hepatitis B virus infection (HBV), large tumor diameter, higher logarithm of Alpha-fetoprotein (Log AFP), higher logarithm of AFP-L3% (Log AFP-L3%), higher logarithm of protein induced by vitamin K absence or antagonist-II (Log PIVKA-II) and higher logarithm of Carbohydrate antigen 125 (Log CA125). The nomogramincorporating these six independent risk factors was finally established. The areas under the ROC curve (AUC) assessed by the nomogram for MVI of HCC in development cohort and validation cohort were 0.806 (95% CI, 0.773～0.839) and 0.818 (95% CI, 0.763～0.874) respectively. The calibration curve revealed that the judged results for MVI of hepatocellular carcinoma using our established diagnostic model were highly consistent with the postoperative pathological results. The decision curve analysis (DCA) showed promising clinical application of the diagnostic nomogram. Moreover, we also found that the diagnostic model had better application value in hepatocellular carcinoma with higher malignancy. Conclusion: An effective preoperative diagnostic model for MVI of HCC based on readily available tumor markers and clinical characters has been established, which can be significant and easily implemented for MVI diagnosis.