Prognostic Value of Non-Invasive Fibrosis and Steatosis Tools, Hepatic Venous Pressure Gradient (HVPG) and Histology in Nonalcoholic Steatohepatitis

BACKGROUND & AIMS: Non-invasive diagnostic methods for liver fibrosis predict clinical outcomes in viral hepatitis and nonalcoholic fatty liver disease (NAFLD). We specifically evaluated prognostic value of non-invasive fibrosis methods in nonalcoholic steatohepatitis (NASH) against hepatic venous pressure gradient (HVPG) and liver histology. METHODS: This was a retrospective cohort study of 148 consecutive patients who met the following criteria: transjugular liver biopsy with HVPG measurement; biopsy-proven NASH; absence of decompensation; AST-to-Platelets Ratio Index (APRI), fibrosis-4 (FIB-4), NAFLD fibrosis score, ultrasound, hepatic steatosis index and Xenon-133 scan available within 6 months from biopsy; a minimum follow-up of 1 year. Outcomes were defined by death, liver transplantation, cirrhosis complications. Kaplan–Meier and Cox regression analyses were employed to estimate incidence and predictors of outcomes, respectively. Prognostic value was expressed as area under the curve (AUC). RESULTS: During a median follow-up of 5 years (interquartile range 3-8), 16.2% developed outcomes, including 7.4% who died or underwent liver transplantation. After adjustment for age, sex, diabetes, the following fibrosis tools predicted outcomes: HVPG >10mmHg (HR=9.60; 95% confidence interval [CI] 3.07-30.12), histologic fibrosis F3-F4 (HR=3.14; 1.41-6.95), APRI >1.5 (HR=5.02; 1.6-15.7), FIB-4 >3.25 (HR=6.33; 1.98-20.2), NAFLD fibrosis score >0.676 (HR=11.9; 3.79-37.4). Prognostic value was as follows: histologic fibrosis stage, AUC=0.85 (95% CI 0.76-0.93); HVPG, AUC=0.81 (0.70-0.91); APRI, AUC=0.89 (0.82-0.96); FIB-4, AUC=0.89 (0.83-0.95); NAFLD fibrosis score, AUC=0.79 (0.69-0.91). Neither histologic steatosis nor non-invasive steatosis methods predicted outcomes (AUC<0.50). CONCLUSIONS: Non-invasive methods for liver fibrosis predict outcomes of patients with NASH. They could be used for serial monitoring, risk stratification and targeted interventions.