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
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 non-alcoholic 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 cut-off 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.
Conclusion: optimal ELF cut-off for ≥F2 is 9.85 and 9.95 for ≥F3. ALT, BMI and HbA1c (ALBA algorithm) can be used to stratify patients at risk of ≥F2. ELF performance is improved by adding ALBA.
diabetes, liver disease, nonalcoholic fatty liver disease (NAFLD), primary health care, retrospective evaluation
800-808
Reinson, Tina
929fcf68-3a7d-42e4-9efd-e9d188b2b9c8
Patel, Janisha
72921b44-d705-4546-a183-90a39432d359
Mathews, Mead
e4e9aace-3aa1-4427-8b62-cfab529eac43
Fountain, Derek
c0ff8670-107e-4144-8a15-548617e70458
Buchanan, Ryan M.
a092c890-492a-478f-8d13-0453d482a700
Byrne, Christopher D.
1370b997-cead-4229-83a7-53301ed2a43c
28 August 2023
Reinson, Tina
929fcf68-3a7d-42e4-9efd-e9d188b2b9c8
Patel, Janisha
72921b44-d705-4546-a183-90a39432d359
Mathews, Mead
e4e9aace-3aa1-4427-8b62-cfab529eac43
Fountain, Derek
c0ff8670-107e-4144-8a15-548617e70458
Buchanan, Ryan M.
a092c890-492a-478f-8d13-0453d482a700
Byrne, Christopher D.
1370b997-cead-4229-83a7-53301ed2a43c
Reinson, Tina, Patel, Janisha, Mathews, Mead, Fountain, Derek, Buchanan, Ryan M. and Byrne, Christopher D.
(2023)
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.
Journal of Clinical and Translational Hepatology, 11 (4), , [JCTH-D-22-00335R1].
(doi:10.14218/JCTH.2022.00335).
Abstract
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 non-alcoholic 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 cut-off 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.
Conclusion: optimal ELF cut-off for ≥F2 is 9.85 and 9.95 for ≥F3. ALT, BMI and HbA1c (ALBA algorithm) can be used to stratify patients at risk of ≥F2. ELF performance is improved by adding ALBA.
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2020LiverClinicPaper_JCTH_AcceptedManuscript
- Accepted Manuscript
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JCTH.2022.0(0).0.00335
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Accepted/In Press date: 26 October 2022
e-pub ahead of print date: 24 February 2023
Published date: 28 August 2023
Additional Information:
Tina Reinson was previously visitor Population Sciences but now visitor HDH, FoM, SGH campus. Aug 28;11(4):800-808
Keywords:
diabetes, liver disease, nonalcoholic fatty liver disease (NAFLD), primary health care, retrospective evaluation
Identifiers
Local EPrints ID: 475737
URI: http://eprints.soton.ac.uk/id/eprint/475737
ISSN: 2225-0719
PURE UUID: c00ad0be-b816-4d5a-a351-0d5b8ad2afea
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Date deposited: 27 Mar 2023 16:44
Last modified: 21 Jul 2023 01:55
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Author:
Tina Reinson
Author:
Janisha Patel
Author:
Mead Mathews
Author:
Derek Fountain
Author:
Ryan M. Buchanan
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