SEARCHCOHORTgastroenterology, endocrinology

cohort·gastroenterology, endocrinology, epidemiology, internal medicine, family medicine·PMC10318295

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 · 6 authors, 6 centres

AI SUMMARY

FIDELITY 100%

POPULATION273 patients referred to a Community Liver Service for vibration-controlled transient elastography (VCTE)

INTERVENTIONEnhanced Liver Fibrosis (ELF) score and a newly developed ALBA algorithm (ALT, BMI, HbA1c)

COMPARISONVibration-controlled transient elastography (VCTE) data as the reference standard for fibrosis staging

This summary was generated by AI from a single paper. It has not been reviewed by a clinician and is not clinical advice. Verify against the source before acting on it.

AGENT 01 · STRUCTURED SUMMARY

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TL;DR

This retrospective study evaluated the performance of the Enhanced Liver Fibrosis (ELF) score and developed a new algorithm (ALBA) using ALT, BMI, and HbA1c to predict significant liver fibrosis (≥F2) in a community-based liver service. The ALBA algorithm showed good performance and combining it with ELF improved prediction accuracy.

Full summary

795 CHARS

This retrospective evaluation assessed 273 patients referred for VCTE to a community liver service between January and December 2020. The study aimed to evaluate the performance of the Enhanced Liver Fibrosis (ELF) score for predicting significant (≥F2) and advanced (≥F3) fibrosis using VCTE as a reference, and to develop a simple predictive algorithm. ELF showed fair performance for both ≥F2 (AUC=0.70) and ≥F3 (AUC=0.72). A new algorithm named ALBA, combining ALT, BMI, and HbA1c, demonstrated good performance for predicting ≥F2 (AUC=0.80). Furthermore, adding the ALBA score to ELF improved the performance for predicting ≥F2 (AUC=0.82). The findings suggest that ALBA can help stratify patients at risk of significant fibrosis and that combining it with ELF enhances predictive accuracy.

PICO

PPOPULATION

273 patients referred to a Community Liver Service for vibration-controlled transient elastography (VCTE)

IINTERVENTION

Enhanced Liver Fibrosis (ELF) score and a newly developed ALBA algorithm (ALT, BMI, HbA1c)

OOUTCOME

Accuracy (AUC) for predicting significant (≥F2) and advanced (≥F3) liver fibrosis

STUDY TYPE

cohort

SPECIALTY

gastroenterology

SUMMARISED BY

AI pipeline

FIDELITY CHECK

100% · A

ORIGINAL PAPER

PMC10318295

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

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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 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.

CITATION EXPORT

Tina Reinson, Janisha Patel, Mead Mathews et al.. 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. (2023). https://doi.org/10.14218/JCTH.2022.00335

AUTHORS

6 · 6 CENTRES

Tina Reinson, Janisha Patel, Mead Mathews, Derek Fountain, Ryan M. Buchanan, Christopher D. Byrne

1Nutrition and Metabolism, Faculty of Medicine, University of Southampton, Southampton, UK
2National Institute for Health and Care Research, Southampton Biomedical Research Center, University Hospital Southampton, Southampton, UK
3Hepatology Department, University Hospital Southampton, Southampton, UK
4St Mary’s Surgery, Southampton, UK
5Core Minutes Ltd, Ringwood, UK
6Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK