Development and validation of a model to predict incident chronic liver disease in the general population: The CLivD score
Fredrik Åberg, Panu K. Luukkonen, Anna But, Veikko Salomaa, Annie Britton, K. Petersen, Stig E. Bojesen, Mie Balling, Børge G. Nordestgaard, Pauli Puukka, Satu Männistö, Annamari Lundqvist, Markus Perola, Antti Jula, Martti Färkkilâ
Abstract
BACKGROUND & AIMS: Current screening strategies for chronic liver disease focus on detection of subclinical advanced liver fibrosis but cannot identify those at high future risk of severe liver disease. Our aim was to develop and validate a risk prediction model for incident chronic liver disease in the general population based on widely available factors. METHODS: ) in 25,760 individuals aged 40-70 years. Their data were sourced from the Finnish population-based health examination surveys FINRISK 1992-2012 and Health 2000 (derivation cohort). The models were externally validated in the Whitehall II (n = 5,058) and Copenhagen City Heart Study (CCHS) (n = 3,049) cohorts. RESULTS: ) in the Whitehall II cohort. CONCLUSIONS: Based on widely available risk factors, the Chronic Liver Disease (CLivD) score can be used to predict risk of future advanced liver disease in the general population. LAY SUMMARY: Liver disease often progresses silently without symptoms and thus the diagnosis is often delayed until severe complications occur and prognosis becomes poor. In order to identify individuals in the general population who have a high risk of developing severe liver disease in the future, we developed and validated a Chronic Liver Disease (CLivD) risk prediction score, based on age, sex, alcohol use, waist-hip ratio, diabetes, and smoking, with or without measurement of the liver enzyme gamma-glutamyltransferase. The CLivD score can be used as part of health counseling, and for planning further liver investigations and follow-up.