Literature DB >> 29154965

Non-invasive assessment of non-alcoholic fatty liver disease: Clinical prediction rules and blood-based biomarkers.

Eduardo Vilar-Gomez1, Naga Chalasani2.   

Abstract

The correct identification of patients at increased risk of non-alcoholic steatohepatitis (NASH) and advanced fibrosis is a critical step in the assessment of non-alcoholic fatty liver disease (NAFLD). Since liver biopsy is invasive, expensive and prone to sampling error, several clinical prediction rules and blood-based biomarkers have been developed as attractive and affordable alternatives for identification of patients at high risk of NASH and advanced fibrosis. Current biomarkers constitute predictive models (e.g. NAFLD fibrosis score, FIB-4 index and BARD score) or direct measures of inflammation (e.g. circulating keratin 18 fragments), or fibrosis (e.g. FibroTest®, ELF™ or Pro-C3 tests). In the clinical setting, biomarkers may discriminate between patients with NASH or advanced fibrosis, predict dynamic changes in NASH/fibrosis over time, and provide long-term prognostic information. Although clinically useful, current biomarker predictions may be influenced by hepatic and extrahepatic conditions (e.g. age, patient comorbidities, and fibrosis or NASH prevalence), which may lead to inaccurate estimates in small subsamples of patients. No highly sensitive and specific tests are available to differentiate NASH from simple steatosis. However, diagnostic accuracy can be improved by combining blood biomarkers. NAFLD fibrosis score and FIB-4 index are both cost-effective and highly sensitive tools to exclude patients with advanced fibrosis. Moreover, their higher scores may identify patients at higher risk of non-liver- and liver-related morbidity and mortality. More expensive tests such as FibroTest or ELF are more specific for detection of patients with significant and advanced fibrosis. Recent efforts have concentrated on "omics" approaches for developing and validating novel biomarkers. Herein, we describe currently available clinical prediction rules and blood-based biomarkers for identifying NASH and advanced fibrosis in patients with NAFLD, discussing their advantages and disadvantages, as well as their potential clinical utility for predicting dynamic changes over time and identifying patients at increased risk of adverse outcomes.
Copyright © 2017 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  APRI; FIB-4; NAFLD; NASH

Mesh:

Substances:

Year:  2017        PMID: 29154965     DOI: 10.1016/j.jhep.2017.11.013

Source DB:  PubMed          Journal:  J Hepatol        ISSN: 0168-8278            Impact factor:   25.083


  130 in total

1.  Clinical Utility of an Increase in Magnetic Resonance Elastography in Predicting Fibrosis Progression in Nonalcoholic Fatty Liver Disease.

Authors:  Veeral H Ajmera; Amy Liu; Seema Singh; Georg Yachoa; Matthew Ramey; Meera Bhargava; Ava Zamani; Scarlett Lopez; Neeraj Mangla; Ricki Bettencourt; Emily Rizo; Mark Valasek; Cynthia Behling; Lisa Richards; Claude Sirlin; Rohit Loomba
Journal:  Hepatology       Date:  2020-01-27       Impact factor: 17.425

2.  Serum metabolites detect the presence of advanced fibrosis in derivation and validation cohorts of patients with non-alcoholic fatty liver disease.

Authors:  Cyrielle Caussy; Veeral H Ajmera; Puneet Puri; Cynthia Li-Shin Hsu; Shirin Bassirian; Mania Mgdsyan; Seema Singh; Claire Faulkner; Mark A Valasek; Emily Rizo; Lisa Richards; David A Brenner; Claude B Sirlin; Arun J Sanyal; Rohit Loomba
Journal:  Gut       Date:  2018-12-19       Impact factor: 23.059

3.  Diagnostic accuracy of combined biomarker measurements and vibration-controlled transient elastography (VCTE) for predicting fibrosis stage of non-alcoholic fatty liver disease.

Authors:  Toshihide Shima; Kyoko Sakai; Hirohisa Oya; Takayuki Katayama; Yasuhide Mitsumoto; Masayuki Mizuno; Yoshihiro Kanbara; Takeshi Okanoue
Journal:  J Gastroenterol       Date:  2019-09-19       Impact factor: 7.527

4.  Diagnostic Accuracy of Shear Wave Elastography as a Non-invasive Biomarker of High-Risk Non-alcoholic Steatohepatitis in Patients with Non-alcoholic Fatty Liver Disease.

Authors:  Arinc Ozturk; Ramin Mohammadi; Theodore T Pierce; Sagar Kamarthi; Manish Dhyani; Joseph R Grajo; Kathleen E Corey; Raymond T Chung; Atul K Bhan; Jagpreet Chhatwal; Anthony E Samir
Journal:  Ultrasound Med Biol       Date:  2020-01-29       Impact factor: 2.998

5.  Development and validation of a nomogram for predicting nonalcoholic fatty liver disease in the non-obese Chinese population.

Authors:  Jiao Wang; Yunliang Tang; Kaili Peng; Honghong Liu; Jixiong Xu
Journal:  Am J Transl Res       Date:  2020-10-15       Impact factor: 4.060

Review 6.  Magnetic Resonance imaging analysis of liver fibrosis and inflammation: overwhelming gray zones restrict clinical use.

Authors:  D Marti-Aguado; A Rodríguez-Ortega; A Alberich-Bayarri; L Marti-Bonmati
Journal:  Abdom Radiol (NY)       Date:  2020-08-28

Review 7.  Pharmacologic Modulation of Bile Acid-FXR-FGF15/FGF19 Pathway for the Treatment of Nonalcoholic Steatohepatitis.

Authors:  Justin D Schumacher; Grace L Guo
Journal:  Handb Exp Pharmacol       Date:  2019

Review 8.  Advances in non-invasive biomarkers for the diagnosis and monitoring of non-alcoholic fatty liver disease.

Authors:  Michelle T Long; Sanil Gandhi; Rohit Loomba
Journal:  Metabolism       Date:  2020-05-05       Impact factor: 8.694

9.  Objective Liver Fibrosis Estimation from Shear Wave Elastography.

Authors:  Laura J Brattain; Brian A Telfer; Manish Dhyani; Joseph R Grajo; Anthony E Samir
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2018-07

Review 10.  Gut microbiota and human NAFLD: disentangling microbial signatures from metabolic disorders.

Authors:  Judith Aron-Wisnewsky; Chloé Vigliotti; Julia Witjes; Phuong Le; Adriaan G Holleboom; Joanne Verheij; Max Nieuwdorp; Karine Clément
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2020-03-09       Impact factor: 46.802

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