Combined use of the ELF test and CLivD score improves prediction of liver-related outcomes in the general population.

Background And Aims: Effective and feasible population screening strategies are needed for the early detection of individuals at high risk of future severe liver-related outcomes. We evaluated the predictive performance of the combination of liver fibrosis assessment, phenotype profile, and genetic risk.

Methods: Data from 5795 adults attending the Finnish Health 2000 Survey were linked with healthcare registers for liver-related outcomes (hospitalization, hepatocellular cancer, and death). Fibrosis was assessed using the enhanced liver fibrosis (ELF) test, phenotype profile by the chronic liver disease (CLivD) risk score, and genetic risk by a validated Polygenic Risk Score (PRS-5). Predictive performance was assessed by competing-risk analyses.

Results: During a median 13-year follow-up, 64 liver-related outcome events were recorded. ELF, CLivD score, and PRS-5 were independently associated with liver-related outcomes. The absolute 10-year risk of liver-related outcomes at an ELF value of 11.3 ranged from 0.3% to 33% depending on the CLivD score. The CLivD score added 51% of new predictive information to the ELF test and improved areas under the curve (AUCs) from 0.91, 0.81, and 0.71 for ELF alone to 0.95, 0.85, and 0.80, respectively, for ELF combined with the CLivD score at 1, 5, and 10 years. The greatest improvement was for 10-year predictions (delta-AUC 0.097, p < .0001). Adding PRS-5 did not significantly increase predictive performance. Findings were consistent in individuals with obesity, diabetes, or alcohol risk use, and regardless of whether gamma-glutamyltransferase was used in the CLivD score.

Conclusion: A combination of ELF and CLivD score predicts liver-related outcomes significantly better than the ELF test alone.