Predictive model for microvascular invasion of hepatocellular carcinoma among candidates for either hepatic resection or liver transplantation

Abstract

BackgroundMicrovascular invasion is the strongest prognostic factor of survival in patients with hepatocellular carcinoma. We therefore developed a predictive model for microvascular invasion of hepatocellular carcinoma to help guide treatment strategies in patients scheduled for either hepatic resection or liver transplantation. MethodsPatients with hepatocellular carcinoma who underwent hepatic resection or liver transplantation from 1994 to 2016 were divided into training and validation cohorts. A predictive model for microvascular invasion was developed based on microvascular invasion risk factors in the training cohort and validated in the validation cohort. ResultsA total of 910 patients (425 having received hepatic resection, 485 having received liver transplantation) were included in the training (n = 637) and validation (n = 273) cohorts. Multivariate analysis identified α-fetoprotein ≥100 ng/mL (relative risk 3.05, P < .0001), tumor size ≥40 mm (relative risk 1.98, P = .0002), nonboundary hepatocellular carcinoma type (relative risk 1.91, P = .001), neutrophil-to-lymphocyte ratio (relative risk 1.86, P = .002), and aspartate aminotransferase (relative risk 1.53, P = .02) as associated with microvascular invasion. The estimated probability of microvascular invasion ranged from 17.0% in patients with none of these factors to 86.9% in the presence of all factors. This model achieved a C-index of 0.732 in the validation cohort. The 5-year overall survival of patients with ≥50% probability of microvascular invasion was poorer than that of patients with <50% probability (hepatic resection; 39.1% vs 61.2%, P < .0001, liver transplantation; 5-year overall survival, 54.8% vs 79.0%, P = .05). ConclusionThis model developed from preoperative data allows reliable prediction of microvascular invasion in candidates for either hepatic resection or liver transplantation.