Combined use of the ELF test and CLivD score improves prediction of liver-related outcomes in the general population.
NAFLD
advanced liver fibrosis
alcohol
cirrhosis
risk prediction
Journal
Liver international : official journal of the International Association for the Study of the Liver
ISSN: 1478-3231
Titre abrégé: Liver Int
Pays: United States
ID NLM: 101160857
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
revised:
12
06
2023
received:
24
04
2023
accepted:
11
07
2023
medline:
19
9
2023
pubmed:
24
7
2023
entrez:
24
7
2023
Statut:
ppublish
Résumé
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. 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. 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. A combination of ELF and CLivD score predicts liver-related outcomes significantly better than the ELF test alone.
Sections du résumé
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.
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2107-2115Informations de copyright
© 2023 The Authors. Liver International published by John Wiley & Sons Ltd.
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