Accuracy of a sequential algorithm based on FIB-4 and ELF to identify high-risk advanced liver fibrosis at the primary care level

Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease, and liver fibrosis is the strongest predictor of morbimortality. We aimed to assess the performance of a sequential algorithm encompassing the Fibrosis 4 (FIB-4) and Enhanced Liver Fibrosis (ELF) scores for iden...

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Bibliographic Details
Authors: Gabriel-Medina, Pablo|||0000-0003-3079-6364, Ferrer Costa, Roser|||0000-0002-8925-3172, Ciudin, Andreea|||0000-0001-5622-0203, Augustin Recio, Salvador|||0000-0002-3515-9033, Rivera Esteban, Jesús|||0000-0003-4357-8817, Pericás, J.M., Martínez Selva, David|||0000-0002-0333-5629, Rodríguez Frías, Francisco|||0000-0002-9128-7013
Format: article
Publication Date:2023
Country:España
Institution:Universitat Autònoma de Barcelona
Repository:Dipòsit Digital de Documents de la UAB
Language:English
OAI Identifier:oai:dnet:uabarcelona_::b11aff98e42bed1980d894ae4182f638
Online Access:https://ddd.uab.cat/record/327182
https://dx.doi.org/urn:doi:10.1007/s11739-023-03441-2
Access Level:Open access
Keyword:Advanced liver fibrosis
NASH
FIB-4
ELF
Type 2 diabetes
Chronic liver disease
Description
Summary:Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease, and liver fibrosis is the strongest predictor of morbimortality. We aimed to assess the performance of a sequential algorithm encompassing the Fibrosis 4 (FIB-4) and Enhanced Liver Fibrosis (ELF) scores for identifying patients at risk of advanced fibrosis. This cross-sectional study included one hospital-based cohort with biopsy-proven NAFLD (n = 140) and two primary care cohorts from different clinical settings: Type 2 Diabetes (T2D) follow-up (n = 141) and chronic liver disease (CLD) initial study (n = 138). Logistic regression analysis was performed to assess liver fibrosis diagnosis models based on FIB-4 and ELF biomarkers. The sequential algorithm retrieved the following accuracy parameters in predicting stages F3-4 in the biopsy-confirmed cohort: sensitivity (85%), specificity (73%), negative predictive value (79%) and positive predictive value (81%). In both T2D and CLD cohorts, a total of 28% of patients were classified as stages F3-4. Furthermore, of all F3-4 classified patients in the T2D cohort, 80% had a diagnosis of liver disease and 44% were referred to secondary care. Likewise, of all F3-4 classified patients in the CLD cohort, 71% had a diagnosis of liver disease and 44% were referred to secondary care. These results suggest the potential utility of this algorithm as a liver fibrosis stratifying tool in primary care, where updating referral protocols to detect high-risk F3-4 is needed. FIB-4 and ELF sequential measurement is an efficient strategy to prioritize patients with high risk of F3-4 in populations with metabolic risk factors.

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