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Performance of the Enhanced Liver Fibrosis Score, Comparison with Vibration-controlled Transient Elastography Data, and Development of a Simple Algorithm to Predict Significant Liver Fibrosis in a Community-based Liver Service: A Retrospective Evaluation

BACKGROUND AND AIMS: Liver fibrosis is a key risk factor for cirrhosis, hepatocellular carcinoma and end stage liver failure. The National Institute for Health and Care Excellence guidelines for assessment for advanced (≥F3) liver fibrosis in people with nonalcoholic fatty liver disease recommend th...

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Autores principales: Reinson, Tina, Patel, Janisha, Mathews, Mead, Fountain, Derek, Buchanan, Ryan M., Byrne, Christopher D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: XIA & HE Publishing Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318295/
https://www.ncbi.nlm.nih.gov/pubmed/37408822
http://dx.doi.org/10.14218/JCTH.2022.00335
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author Reinson, Tina
Patel, Janisha
Mathews, Mead
Fountain, Derek
Buchanan, Ryan M.
Byrne, Christopher D.
author_facet Reinson, Tina
Patel, Janisha
Mathews, Mead
Fountain, Derek
Buchanan, Ryan M.
Byrne, Christopher D.
author_sort Reinson, Tina
collection PubMed
description BACKGROUND AND AIMS: Liver fibrosis is a key risk factor for cirrhosis, hepatocellular carcinoma and end stage liver failure. The National Institute for Health and Care Excellence guidelines for assessment for advanced (≥F3) liver fibrosis in people with nonalcoholic fatty liver disease recommend the use of enhanced liver fibrosis (ELF) test, followed by vibration-controlled transient elastography (VCTE). Performance of ELF at predicting significant (≥F2) fibrosis in real-world practice is uncertain. To assess the accuracy of ELF using VCTE; investigate the optimum ELF cutoff value to identify ≥F2 and ≥F3; and develop a simple algorithm, with and without ELF score, for detecting ≥F2. METHODS: Retrospective evaluation of patients referred to a Community Liver Service for VCTE, Jan-Dec 2020. Assessment included: body mass index (BMI), diabetes status, alanine aminotransferase (ALT) levels, ELF score and biopsy-validated fibrosis stages according to VCTE. RESULTS: Data from 273 patients were available. n=110 patients had diabetes. ELF showed fair performance for ≥F2 and ≥F3, area under the curve (AUC) = 0.70, 95% confidence interval (CI) 0.64–0.76 and AUC=0.72, 95% CI: 0.65–0.79 respectively. For ≥F2 Youden’s index for ELF=9.85 and for ≥F3, ELF=9.95. Combining ALT, BMI, and HbA1c (ALBA algorithm) to predict ≥F2 showed good performance (AUC=0.80, 95% CI: 0.69–0.92), adding ALBA to ELF improved performance (AUC=0.82, 95% CI: 0.77–0.88). Results were independently validated. CONCLUSIONS: Optimal ELF cutoff for ≥F2 is 9.85 and 9.95 for ≥F3. ALT, BMI, and HbA1c (ALBA algorithm) can stratify patients at risk of ≥F2. ELF performance is improved by adding ALBA.
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spelling pubmed-103182952023-07-05 Performance of the Enhanced Liver Fibrosis Score, Comparison with Vibration-controlled Transient Elastography Data, and Development of a Simple Algorithm to Predict Significant Liver Fibrosis in a Community-based Liver Service: A Retrospective Evaluation Reinson, Tina Patel, Janisha Mathews, Mead Fountain, Derek Buchanan, Ryan M. Byrne, Christopher D. J Clin Transl Hepatol Original Article BACKGROUND AND AIMS: Liver fibrosis is a key risk factor for cirrhosis, hepatocellular carcinoma and end stage liver failure. The National Institute for Health and Care Excellence guidelines for assessment for advanced (≥F3) liver fibrosis in people with nonalcoholic fatty liver disease recommend the use of enhanced liver fibrosis (ELF) test, followed by vibration-controlled transient elastography (VCTE). Performance of ELF at predicting significant (≥F2) fibrosis in real-world practice is uncertain. To assess the accuracy of ELF using VCTE; investigate the optimum ELF cutoff value to identify ≥F2 and ≥F3; and develop a simple algorithm, with and without ELF score, for detecting ≥F2. METHODS: Retrospective evaluation of patients referred to a Community Liver Service for VCTE, Jan-Dec 2020. Assessment included: body mass index (BMI), diabetes status, alanine aminotransferase (ALT) levels, ELF score and biopsy-validated fibrosis stages according to VCTE. RESULTS: Data from 273 patients were available. n=110 patients had diabetes. ELF showed fair performance for ≥F2 and ≥F3, area under the curve (AUC) = 0.70, 95% confidence interval (CI) 0.64–0.76 and AUC=0.72, 95% CI: 0.65–0.79 respectively. For ≥F2 Youden’s index for ELF=9.85 and for ≥F3, ELF=9.95. Combining ALT, BMI, and HbA1c (ALBA algorithm) to predict ≥F2 showed good performance (AUC=0.80, 95% CI: 0.69–0.92), adding ALBA to ELF improved performance (AUC=0.82, 95% CI: 0.77–0.88). Results were independently validated. CONCLUSIONS: Optimal ELF cutoff for ≥F2 is 9.85 and 9.95 for ≥F3. ALT, BMI, and HbA1c (ALBA algorithm) can stratify patients at risk of ≥F2. ELF performance is improved by adding ALBA. XIA & HE Publishing Inc. 2023-08-28 2023-02-24 /pmc/articles/PMC10318295/ /pubmed/37408822 http://dx.doi.org/10.14218/JCTH.2022.00335 Text en © 2023 Authors. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 4.0 International License (CC BY-NC 4.0), permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Reinson, Tina
Patel, Janisha
Mathews, Mead
Fountain, Derek
Buchanan, Ryan M.
Byrne, Christopher D.
Performance of the Enhanced Liver Fibrosis Score, Comparison with Vibration-controlled Transient Elastography Data, and Development of a Simple Algorithm to Predict Significant Liver Fibrosis in a Community-based Liver Service: A Retrospective Evaluation
title Performance of the Enhanced Liver Fibrosis Score, Comparison with Vibration-controlled Transient Elastography Data, and Development of a Simple Algorithm to Predict Significant Liver Fibrosis in a Community-based Liver Service: A Retrospective Evaluation
title_full Performance of the Enhanced Liver Fibrosis Score, Comparison with Vibration-controlled Transient Elastography Data, and Development of a Simple Algorithm to Predict Significant Liver Fibrosis in a Community-based Liver Service: A Retrospective Evaluation
title_fullStr Performance of the Enhanced Liver Fibrosis Score, Comparison with Vibration-controlled Transient Elastography Data, and Development of a Simple Algorithm to Predict Significant Liver Fibrosis in a Community-based Liver Service: A Retrospective Evaluation
title_full_unstemmed Performance of the Enhanced Liver Fibrosis Score, Comparison with Vibration-controlled Transient Elastography Data, and Development of a Simple Algorithm to Predict Significant Liver Fibrosis in a Community-based Liver Service: A Retrospective Evaluation
title_short Performance of the Enhanced Liver Fibrosis Score, Comparison with Vibration-controlled Transient Elastography Data, and Development of a Simple Algorithm to Predict Significant Liver Fibrosis in a Community-based Liver Service: A Retrospective Evaluation
title_sort performance of the enhanced liver fibrosis score, comparison with vibration-controlled transient elastography data, and development of a simple algorithm to predict significant liver fibrosis in a community-based liver service: a retrospective evaluation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10318295/
https://www.ncbi.nlm.nih.gov/pubmed/37408822
http://dx.doi.org/10.14218/JCTH.2022.00335
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