P-18 ANTI-HBC POSITIVITY IS AN INDEPENDENT PREDICTIVE FACTOR FOR HCC DEVELOPMENT AND SHOULD BE INCORPORATED TO THE HCC RISK SCORE PREDICTION MODEL IN ADVANCED FIBROSIS

No After hepatitis C virus (HCV) treatment with direct-acting antivirals (DAAs), the sustained viral response increased to 95%, although it may be lower in advanced fibrosis. Continuous follow-up of HCV cured individuals is essential. In that context, identifying higher risk populations to intensify its surveillance is important to allow early hepatocellular carcinoma (HCC) detection and optimize costs. Our group previously demonstrated a risk association between anti-HBc and HCC, since the presence of hepatitis B virus infection has oncogenic properties. Our objective is to evaluate the HCC risk score prediction model accuracy in our population and investigate the inclusion of anti-HBc positivity in the model. This is a retrospective, observational, descriptive and analytic study in a series of cases in which 365 HCV patients were evaluated. Demographic, clinical and laboratory data were obtained through electronic medical records. The HCC risk score was applied before and after SVR. A total of 21 patients had HCC diagnosis after RVS (5.75%). The variables associated with higher HCC occurrence were: genotype 3 (p=0.025), AST pretreatment (p=0.026), elastography > 10kPa (p=0.003) and advanced fibrosis (p=0.016). Among advanced fibrosis patients, positive Anti-HBc (p=0.047) was an independent predictor factor associated with HCC. After univariated analysis, genotype 3 and positive anti-HBc were predictive factors of HCC occurrence in advanced fibrosis. When applying the HCC risk score before treatment, the area under the receiver operating characteristic curve (AUROC) was 0.731, while after SVR had a slightly lower value (0.723) – Figure 1A. After incorporating anti-HBc to all other variables used in HCC risk score, the accuracy was 0.744 – Figure 1B. The HCC risk score is a validated prediction model of HCC occurrence before and after SVR. Anti-HBc positivity might be a good candidate to be incorporated to the model.