Various factors are associated with the prognosis of patients with non-viral hepatocellular carcinoma (HCC). The present study aimed to investigate the prognosis of patients with non-viral HCC compared with that of patients with hepatitis C virus-related (HCV)-HCC and the features associated with prognosis of patients with non-viral HCC using data mining analyses. Patients with non-viral HCC (n=182, age 70.4±8.9 years) and HCV-HCC (n=612, age 70±8.4 years) were enrolled and the overall survival was compared between the non-viral HCC and HCV-HCC groups. The present study performed random forest and decision tree analyses to identify features that distinguish prognosis between the non-viral HCC and HCV-HCC groups. The median survival of the non-viral HCC group was significantly shorter than the HCV-HCC group (1,553 vs. 2,304 days, P<0.01). In the multivariate analysis, the non-viral HCC group was an independent risk factor for survival (HR 1.42, 95% CI 1.08-1.87, P=0.013). In the random forest analysis, the high-ranking distinguishable factors were 'number of tumors' and 'HCC stage' in the non-viral HCC group and 'albumin' and 'total bilirubin' in the HCV-HCC group. The decision tree analysis revealed that, in patients with HCC stage >I, the survival period in the non-viral HCC group was significantly shorter than the HCV-HCC group (HR 1.39, 95% CI 1.07-1.81, P=0.0132). The prognosis of patients with non-viral HCC was poorer than patients with HCV-HCC. In addition, data mining analysis revealed that tumor-related variables had the highest importance for survival in patients with non-viral HCC.
Keywords: artificial intelligence approach; hepatoma; non-hepatitis B and non-hepatitis C virus; prognosis; prognostic factors.