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Wing-Sun Chow 1 Article
Clinical Study
Development of a Non-Invasive Liver Fibrosis Score Based on Transient Elastography for Risk Stratification in Patients with Type 2 Diabetes
Chi-Ho Lee, Wai-Kay Seto, Kelly Ieong, David T.W. Lui, Carol H.Y. Fong, Helen Y. Wan, Wing-Sun Chow, Yu-Cho Woo, Man-Fung Yuen, Karen S.L. Lam
Endocrinol Metab. 2021;36(1):134-145.   Published online February 24, 2021
DOI: https://doi.org/10.3803/EnM.2020.887
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  • 5 Web of Science
  • 6 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
In non-alcoholic fatty liver disease (NAFLD), transient elastography (TE) is an accurate non-invasive method to identify patients at risk of advanced fibrosis (AF). We developed a diabetes-specific, non-invasive liver fibrosis score based on TE to facilitate AF risk stratification, especially for use in diabetes clinics where TE is not readily available.
Methods
Seven hundred sixty-six adults with type 2 diabetes and NAFLD were recruited and randomly divided into a training set (n=534) for the development of diabetes fibrosis score (DFS), and a testing set (n=232) for internal validation. DFS identified patients with AF on TE, defined as liver stiffness (LS) ≥9.6 kPa, based on a clinical model comprising significant determinants of LS with the lowest Akaike information criteria. The performance of DFS was compared with conventional liver fibrosis scores (NFS, FIB-4, and APRI), using area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive and negative predictive values (NPV).
Results
DFS comprised body mass index, platelet, aspartate aminotransferase, high-density lipoprotein cholesterol, and albuminuria, five routine measurements in standard diabetes care. Derived low and high DFS cut-offs were 0.1 and 0.3, with 90% sensitivity and 90% specificity, respectively. Both cut-offs provided better NPVs of >90% than conventional fibrosis scores. The AUROC of DFS for AF on TE was also higher (P<0.01) than the conventional fibrosis scores, being 0.85 and 0.81 in the training and testing sets, respectively.
Conclusion
Compared to conventional fibrosis scores, DFS, with a high NPV, more accurately identified diabetes patients at-risk of AF, who need further evaluation by hepatologists.

Citations

Citations to this article as recorded by  
  • Implementation of a liver health check in people with type 2 diabetes
    Kushala W M Abeysekera, Luca Valenti, Zobair Younossi, John F Dillon, Alina M Allen, Mazen Noureddin, Mary E Rinella, Frank Tacke, Sven Francque, Pere Ginès, Maja Thiele, Philip N Newsome, Indra Neil Guha, Mohammed Eslam, Jörn M Schattenberg, Saleh A Alqa
    The Lancet Gastroenterology & Hepatology.2024; 9(1): 83.     CrossRef
  • Sequential algorithm to stratify liver fibrosis risk in overweight/obese metabolic dysfunction-associated fatty liver disease
    Chi-Ho Lee, David Tak-Wai Lui, Raymond Hang-Wun Li, Michele Mae-Ann Yuen, Carol Ho-Yi Fong, Ambrose Pak-Wah Leung, Justin Chiu-Man Chu, Loey Lung-Yi Mak, Tai-Hing Lam, Jean Woo, Yu-Cho Woo, Aimin Xu, Hung-Fat Tse, Kathryn Choon-Beng Tan, Bernard Man-Yung
    Frontiers in Endocrinology.2023;[Epub]     CrossRef
  • Non-Invasive Measurement of Hepatic Fibrosis by Transient Elastography: A Narrative Review
    Luca Rinaldi, Chiara Giorgione, Andrea Mormone, Francesca Esposito, Michele Rinaldi, Massimiliano Berretta, Raffaele Marfella, Ciro Romano
    Viruses.2023; 15(8): 1730.     CrossRef
  • Metabolic dysfunction-associated fatty liver disease — How relevant is this to primary care physicians and diabetologists?
    Chi-Ho Lee
    Primary Care Diabetes.2022; 16(2): 245.     CrossRef
  • Non‐alcoholic fatty liver disease and type 2 diabetes: An update
    Chi‐H Lee, David TW Lui, Karen SL Lam
    Journal of Diabetes Investigation.2022; 13(6): 930.     CrossRef
  • Ultrasound-Based Hepatic Elastography in Non-Alcoholic Fatty Liver Disease: Focus on Patients with Type 2 Diabetes
    Georgiana-Diana Cazac, Cristina-Mihaela Lăcătușu, Cătălina Mihai, Elena-Daniela Grigorescu, Alina Onofriescu, Bogdan-Mircea Mihai
    Biomedicines.2022; 10(10): 2375.     CrossRef
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