MAFLD fibrosis score: Using routine measures to identify advanced fibrosis in metabolic-associated fatty liver disease.
Journal
Alimentary pharmacology & therapeutics
ISSN: 1365-2036
Titre abrégé: Aliment Pharmacol Ther
Pays: England
ID NLM: 8707234
Informations de publication
Date de publication:
12 2023
12 2023
Historique:
revised:
06
08
2023
received:
11
07
2023
accepted:
07
09
2023
medline:
22
11
2023
pubmed:
19
9
2023
entrez:
19
9
2023
Statut:
ppublish
Résumé
Early screening may prevent fibrosis progression in metabolic-associated fatty liver disease (MAFLD). We developed and validated MAFLD fibrosis score (MFS) for identifying advanced fibrosis (≥F3) among MAFLD patients. This cross-sectional, multicentre study consecutively recruited MAFLD patients receiving tertiary care (Malaysia as training cohort [n = 276] and Hong Kong and Wenzhou as validation cohort [n = 431]). Patients completed liver biopsy, vibration-controlled transient elastography (VCTE), and clinical and laboratory assessment within 1 week. We used machine learning to select 'highly important' predictors of advanced fibrosis, followed by backward stepwise regression to construct MFS formula. MFS was composed of seven variables: age, body mass index, international normalised ratio, aspartate aminotransferase, gamma-glutamyl transpeptidase, platelet count, and history of type 2 diabetes. MFS demonstrated an area under the receiver-operating characteristic curve of 0.848 [95% CI 0.800-898] and 0.823 [0.760-0.886] in training and validation cohorts, significantly higher than aminotransferase-to-platelet ratio index (0.684 [0.603-0.765], 0.663 [0.588-0.738]), Fibrosis-4 index (0.793 [0.735-0.854], 0.737 [0.660-0.814]), and non-alcoholic fatty liver disease fibrosis score (0.785 [0.731-0.844], 0.750 [0.674-0.827]) (DeLong's test p < 0.05). MFS could include 92.3% of patients using dual cut-offs of 14 and 15, with a correct prediction rate of 90.4%, resulting in a larger number of patients with correct diagnosis compared to other scores. A two-step MFS-VCTE screening algorithm demonstrated positive and negative predictive values and overall diagnostic accuracy of 93.4%, 89.5%, and 93.2%, respectively, with only 4.0% of patients classified into grey zone. MFS outperforms conventional non-invasive scores in predicting advanced fibrosis, contributing to screening in MAFLD patients.
Sections du résumé
BACKGROUND
Early screening may prevent fibrosis progression in metabolic-associated fatty liver disease (MAFLD).
AIMS
We developed and validated MAFLD fibrosis score (MFS) for identifying advanced fibrosis (≥F3) among MAFLD patients.
METHODS
This cross-sectional, multicentre study consecutively recruited MAFLD patients receiving tertiary care (Malaysia as training cohort [n = 276] and Hong Kong and Wenzhou as validation cohort [n = 431]). Patients completed liver biopsy, vibration-controlled transient elastography (VCTE), and clinical and laboratory assessment within 1 week. We used machine learning to select 'highly important' predictors of advanced fibrosis, followed by backward stepwise regression to construct MFS formula.
RESULTS
MFS was composed of seven variables: age, body mass index, international normalised ratio, aspartate aminotransferase, gamma-glutamyl transpeptidase, platelet count, and history of type 2 diabetes. MFS demonstrated an area under the receiver-operating characteristic curve of 0.848 [95% CI 0.800-898] and 0.823 [0.760-0.886] in training and validation cohorts, significantly higher than aminotransferase-to-platelet ratio index (0.684 [0.603-0.765], 0.663 [0.588-0.738]), Fibrosis-4 index (0.793 [0.735-0.854], 0.737 [0.660-0.814]), and non-alcoholic fatty liver disease fibrosis score (0.785 [0.731-0.844], 0.750 [0.674-0.827]) (DeLong's test p < 0.05). MFS could include 92.3% of patients using dual cut-offs of 14 and 15, with a correct prediction rate of 90.4%, resulting in a larger number of patients with correct diagnosis compared to other scores. A two-step MFS-VCTE screening algorithm demonstrated positive and negative predictive values and overall diagnostic accuracy of 93.4%, 89.5%, and 93.2%, respectively, with only 4.0% of patients classified into grey zone.
CONCLUSION
MFS outperforms conventional non-invasive scores in predicting advanced fibrosis, contributing to screening in MAFLD patients.
Types de publication
Multicenter Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1194-1204Subventions
Organisme : Chinese University of Hong Kong
ID : Direct Grant (2022.031)
Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2023 The Authors. Alimentary Pharmacology & Therapeutics published by John Wiley & Sons Ltd.
Références
Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global epidemiology of nonalcoholic fatty liver disease-meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016;64(1):73-84. https://doi.org/10.1002/hep.28431
Zhang X, Goh GB-B, Chan W-K, Wong GLH, Fan JG, Seto WK, et al. Unhealthy lifestyle habits and physical inactivity among Asian patients with non-alcoholic fatty liver disease. Liver Int. 2020;40(11):2719-2731. https://doi.org/10.1111/liv.14638
Powell EE, Wong VW-S, Rinella M. Non-alcoholic fatty liver disease. Lancet. 2021;397(10290):2212-2224. https://doi.org/10.1016/S0140-6736(20)32511-3
Zhang X, Wong GL-H, Wong VW-S. Application of transient elastography in nonalcoholic fatty liver disease. Clin Mol Hepatol. 2020;26(2):128-141. https://doi.org/10.3350/cmh.2019.0001n
Younossi ZM, Blissett D, Blissett R, Henry L, Stepanova M, Younossi Y, et al. The economic and clinical burden of nonalcoholic fatty liver disease in the United States and Europe. Hepatology. 2016;64(5):1577-1586. https://doi.org/10.1002/hep.28785
Kleiner DE, Brunt EM, van Natta M, Behling C, Contos MJ, Cummings OW, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41(6):1313-1321. https://doi.org/10.1002/hep.20701
Wai CT, Greenson JK, Fontana RJ, Kalbfleisch JD, Marrero JA, Conjeevaram HS, et al. A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology. 2003;38(2):518-526. https://doi.org/10.1053/jhep.2003.50346
Sterling RK, Lissen E, Clumeck N, Sola R, Correa MC, Montaner J, et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology. 2006;43(6):1317-1325. https://doi.org/10.1002/hep.21178
Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology. 2007;45(4):846-854. https://doi.org/10.1002/hep.21496
Mahady SE, Macaskill P, Craig JC, Wong GLH, Chu WCW, Chan HLY, et al. Diagnostic accuracy of noninvasive fibrosis scores in a population of individuals with a low prevalence of fibrosis. Clin Gastroenterol Hepatol. 2017;15(9):1453-1460.e1. https://doi.org/10.1016/j.cgh.2017.02.031
Adams LA, George J, Bugianesi E, Rossi E, de Boer WB, van der Poorten D, et al. Complex non-invasive fibrosis models are more accurate than simple models in non-alcoholic fatty liver disease. J Gastroenterol Hepatol. 2011;26(10):1536-1543. https://doi.org/10.1111/j.1440-1746.2011.06774.x
Brunt EM, Janney CG, Di Bisceglie AM, Neuschwander-Tetri BA, Bacon BR. Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions. Am J Gastroenterol. 1999;94(9):2467-2474. https://doi.org/10.1111/j.1572-0241.1999.01377.x
Wong VWS, Irles M, Wong GLH, Shili S, Chan AWH, Merrouche W, et al. Unified interpretation of liver stiffness measurement by M and XL probes in non-alcoholic fatty liver disease. Gut. 2019;68(11):2057-2064. https://doi.org/10.1136/gutjnl-2018-317334
Kursa MB, Rudnicki WR. Feature selection with the Boruta package. J Stat Softw. 2010;36(11 SE-Articles):1-13. https://doi.org/10.18637/jss.v036.i11
Kanwal F, Shubrook JH, Adams LA, Pfotenhauer K, Wai-Sun Wong V, Wright E, et al. Clinical care pathway for the risk stratification and management of patients with nonalcoholic fatty liver disease. Gastroenterology. 2021;161(5):1657-1669. https://doi.org/10.1053/j.gastro.2021.07.049
Sanyal AJ, Foucquier J, Younossi ZM, Harrison SA, Newsome PN, Chan WK, et al. Enhanced diagnosis of advanced fibrosis and cirrhosis in individuals with NAFLD using FibroScan-based agile scores. J Hepatol. 2023;78(2):247-259. https://doi.org/10.1016/j.jhep.2022.10.034
Mózes FE, Lee JA, Selvaraj EA, Jayaswal ANA, Trauner M, Boursier J, et al. Diagnostic accuracy of non-invasive tests for advanced fibrosis in patients with NAFLD: an individual patient data meta-analysis. Gut. 2022;71(5):1006-1019. https://doi.org/10.1136/gutjnl-2021-324243
Xia M-F, Bian H, Gao X. NAFLD and diabetes: two sides of the same coin? Rationale for gene-based personalized NAFLD treatment. Front Pharmacol. 2019;10:877. https://doi.org/10.3389/fphar.2019.00877
Younossi ZM, Golabi P, de Avila L, Paik JM, Srishord M, Fukui N, et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: a systematic review and meta-analysis. J Hepatol. 2019;71(4):793-801. https://doi.org/10.1016/j.jhep.2019.06.021
Alam S, Noor-E-Alam SM, Chowdhury ZR, Alam M, Kabir J. Nonalcoholic steatohepatitis in nonalcoholic fatty liver disease patients of Bangladesh. World J Hepatol. 2013;5(5):281-287. https://doi.org/10.4254/wjh.v5.i5.281
Ma Q, Liao X, Shao C, Lin Y, Wu T, Sun Y, et al. Normalization of γ-glutamyl transferase levels is associated with better metabolic control in individuals with nonalcoholic fatty liver disease. BMC Gastroenterol. 2021;21(1):215. https://doi.org/10.1186/s12876-021-01790-w
Lemoine M, Shimakawa Y, Nayagam S, Khalil M, Suso P, Lloyd J, et al. The gamma-glutamyl transpeptidase to platelet ratio (GPR) predicts significant liver fibrosis and cirrhosis in patients with chronic HBV infection in West Africa. Gut. 2016;65(8):1369-1376. https://doi.org/10.1136/gutjnl-2015-309260
European Association for the Study of the liver (EASL), European Association for the Study of diabetes (EASD), European Association for the Study of obesity (EASO). Clinical practice guidelines for the management of non-alcoholic fatty liver disease. J Hepatol. 2016;64(6):1388-1402. https://doi.org/10.1016/j.jhep.2015.11.004
Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology. 2018;67(1):328-357. https://doi.org/10.1002/hep.29367
Eslam M, Sarin SK, Wong VW-S, Fan JG, Kawaguchi T, Ahn SH, et al. The Asian Pacific Association for the Study of the liver clinical practice guidelines for the diagnosis and management of metabolic associated fatty liver disease. Hepatol Int. 2020;14(6):889-919. https://doi.org/10.1007/s12072-020-10094-2
Berger D, Desai V, Janardhan S. Con: liver biopsy remains the gold standard to evaluate fibrosis in patients with nonalcoholic fatty liver disease. Clin Liver Dis. 2019;13(4):114-116. https://doi.org/10.1002/cld.740
Brunt EM. Pathology of fatty liver disease. Mod Pathol. 2007;20(1):S40-S48. https://doi.org/10.1038/modpathol.3800680