Improved prediction of 10-year risk of severe liver disease in the general population using commonly available biomarkers

BackgroundEstimating the risk for cirrhosis in the general population is complex. Existing prediction tools are in general unsatisfactory. AimsTo explore if using commonly available biomarkers can improve the commonly used FIB-4 score in the identification of subgroups at risk of cirrhosis. MethodsWe used laboratory and clinical data on 126,925 individuals aged 35-79 years in Stockholm, Sweden, undergoing health examinations from 1985 to 1996. We used Swedish nationwide registries to ascertain 10-year cumulative incidence of severe liver disease, a composite of diagnoses corresponding to cirrhosis and its complications. We considered combinations of biomarkers associated with severe liver disease to identify subgroups with different risk profiles. ResultsDuring an average follow-up of 9.3 years, we ascertained 630 incident cases of severe liver disease (0.5%). Age, the FIB-4 score, diabetes or impaired glucose and gamma-glutamyl transferase (gGT) were the most relevant characteristics for classifying risk profiles. Using these factors, we identified 24 groups with a cumulative incidence of severe liver disease at 10 years ranging from 0.2% (age 35-65, low FIB-4, no diabetes or impaired glucose and normal gGT) to 32.1% (age 35-65, high FIB-4, diabetes or impaired glucose and high gGT). ConclusionsIdentification of subjects at increased risk of severe liver disease in the general population using the FIB-4 score can be substantially improved by adding age and specific biomarkers commonly available in the primary care setting. These parameters should be considered for inclusion in the development of future risk prediction models.

Automated summary

This study aims to improve the commonly used FIB-4 score in identifying subgroups at risk of cirrhosis by using commonly available biomarkers. The results show that the accuracy of identifying severe liver disease risk can be significantly improved by combining age and specific biomarkers with the FIB-4 score.