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Validation of the Hepamet fibrosis score in a multi-ethnic Asian population
Affiliation:1. Gastroenterology and Hepatology Unit, Department of Medicine, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia;2. Clinical Diagnostic Laboratory, Department of Pathology, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia;3. Department of Pathology, Hospital Sultanah Bahiyah, 05460 Alor Setar, Kedah, Malaysia
Abstract:Introduction and ObjectivesThe Hepamet fibrosis score was introduced for the diagnosis of advanced liver fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). To date, external validation is limited, and its utility in combination with liver stiffness measurement (LSM) has not been explored.Material and MethodsThis is a cross-sectional study on NAFLD patients who had a liver biopsy and LSM on the same day. The diagnostic performance of the Hepamet fibrosis score was evaluated using the area under the receiver operating characteristic curve (AUROC).ResultsThe data for 196 patients were analyzed (mean age 50 ± 11 years old, 50% men, 56.6% Malay, 27.6% Chinese, 15.8% Indian, 67.9% NASH, 15.8% advanced liver fibrosis). The AUROC of Hepamet fibrosis score for the diagnosis of advanced liver fibrosis was 0.85 (95% CI, 0.80 – 0.91). Using the <0.12 and ≥0.47 cut-offs from the original study, the sensitivity, specificity, positive predictive value, negative predictive value, the proportion of indeterminate results and misclassification rate were 81.8%, 91.8%, 47.4%, 98.2%, 32.1% and 6.1%, respectively. Using LSM <10 kPa and ≥15 kPa for the diagnosis of absence and presence of advanced liver fibrosis, respectively, in patients with Hepamet fibrosis score ≥0.47 (i.e., the two-step approach) reduced indeterminate results and misclassification to 16.1% and 3.6%, respectively.ConclusionsWe found the Hepamet fibrosis score to have good diagnostic accuracy in a population that was largely unrepresented in earlier work and demonstrated its utility in a two-step approach with LSM for the diagnosis of advanced liver fibrosis.
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