A Genetic and Metabolic Staging System for Predicting the Outcome of Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is an emerging cause of liver-related events (LREs). Here, we have assessed the ability of a composite score based on clinical features, metabolic comorbidities, and genetic variants to predict LREs. A total of 546 consecutive patients with NAFLD were recruited and stratified according to the fibrosis-4 (FIB-4) index. LREs were defined as occurrence of hepatocellular carcinoma or hepatic decompensation. Cox regression multivariate analysis was used to identify baseline variables associated with LREs. The UK Biobank was used as the validation cohort, and severe liver disease (incidence of cirrhosis, decompensated liver disease, hepatocellular carcinoma, and/or liver transplantation) was used as the outcome. LREs were experienced by 58 patients, only one of whom was in the cohort of patients with a FIB-4 score < 1.3. Multivariate Cox regression analysis of 229 patients with a FIB-4 score >= 1.3 highlighted clinical variables independently associated with the development of LREs, including older age, low platelet count, low albumin, low high-density lipoprotein cholesterol, certain genetic factors, and interactions between genetic factors and sex or diabetes. The area under the curve (AUC) for the model was 0.87 at 1, 3, and 5 years. Our novel Genetic and Metabolic Staging (GEMS) scoring system was derived from the Cox model linear predictor, ranked from 0 to 10, and categorized into five classes (0-5, 5-6, 6-7, 7-8, and 8-10). The risk of LREs increased from 4% in patients in the best class (GEMS score 0-5) to 91% in the worst (GEMS score 8-10). GEMS score was associated with incident severe liver disease in the study population (hazard ratio, 1.56; 95% confidence interval, 1.48-1.65; P < 0.001) as well as in the UK Biobank cohort where AUCs for prediction of severe liver disease at 1, 3, and 5 years were 0.70, 0.69, and 0.67, respectively. Conclusion: The novel GEMS scoring system has an adequate ability to predict the outcome of patients with NAFLD.