Use of new CORE risk score to predict 10 year risk of liver cirrhosis in general population: population based cohort study

Abstract Objective To develop and validate a novel risk prediction model for incident major adverse liver outcomes (MALO) in a primary care setting. Design Population based cohort study. Setting Sweden, with validation in Finland and the UK. Participants Model development in 480 651 individuals with no known history of liver disease and blood tests taken in primary care or at occupational healthcare screenings; validation in two cohorts with 24 191 and 449 806 individuals without known history of liver disease. Main outcome measures 10 year risk of a composite outcome of compensated and decompensated cirrhosis, hepatocellular carcinoma, liver transplant, and liver related mortality, collectively referred to as MALO. Results A new risk model was created using flexible parametric survival models and several easily available laboratory based biomarkers. The model includes age, sex, aspartate aminotransferase, alanine aminotransferase, and γ-glutamyl transferase. The model’s performance was assessed in terms of discrimination (time dependent area under the curve), calibration (calibration curves), and clinical utility (decision curve analysis). External validation was done using data from the UK Biobank and the FINRISK and Health 2000 cohorts and compared with the FIB-4 score. The median follow-up time was 28 years, and 7168 MALO events were observed in that time. The incident risk of MALO at 10 years was 0.27%. The new risk score, termed CORE (Cirrhosis Outcome Risk Estimator), achieved a 10 year area under the curve of 88% (95% confidence interval 87% to 89%) compared with 79% (78% to 80%) for FIB-4. The calibration of CORE was good in all three cohorts, and according to the decision curve analysis CORE provides a higher net benefit than FIB-4 for all risk thresholds. Conclusions The CORE model, based on a flexible modelling approach and using biomarkers easily accessible in primary care, outperforms FIB-4 when predicting liver related outcomes in the general population and could be a novel means to stratify patients at risk for liver disease in the general population.