Literature DB >> 28286195

Diagnostic Accuracy of Noninvasive Fibrosis Scores in a Population of Individuals With a Low Prevalence of Fibrosis.

Suzanne E Mahady1, Petra Macaskill2, Jonathan C Craig3, Grace L H Wong4, Winnie C W Chu5, Henry L Y Chan4, Jacob George6, Vincent W S Wong7.   

Abstract

BACKGROUND & AIMS: Noninvasive scoring systems for fibrosis are increasingly used in the clinic and in research because of their ease of use, accessibility, and low cost. However, test performance characteristics were established in groups of patients with a high prevalence of advanced fibrosis; little is known about diagnostic accuracy in low-risk populations.
METHODS: In a cross-sectional study, 922 members of a general ambulatory population in Hong Kong (randomly selected; 18-70 years old) underwent clinical assessment from May 2008 through December 2010. All participants completed a standard questionnaire that collected information on age, sex, and history of smoking and alcohol use. Results of fasting blood tests and transient elastography were used as the reference standard to identify patients with advanced fibrosis. We assessed performance characteristics of 3 noninvasive fibrosis scoring systems: the nonalcoholic fatty liver disease fibrosis scoring system, the Fibrosis-4 scoring system, and aspartate transaminase to platelet ratio index, using standard thresholds. To calculate diagnostic test characteristics, we constructed a 2-by-2 table with the presence or absence of advanced fibrosis according to the transient elastography reading against the presence or absence of advanced fibrosis according to the scoring systems. Area under the receiver operating curve was calculated to assess overall diagnostic accuracy.
RESULTS: Of the 922 individuals evaluated by transient elastography, 749 had a valid reading and 15 had advanced fibrosis (2%). The specificity of noninvasive scores in detection of advanced fibrosis approximated 100% (95% confidence interval [CI], 99%-100%), with a negative predictive value of 98% (95% CI, 97%-99%) for all systems. However, the scoring systems detected fibrosis with a low level of sensitivity, ranging from 7% (95% CI, 0%-32%) to 13% (95% CI, 2%-40%). Positive predictive values ranged from 50% (95% CI, 7%-93%) to 67% (95% CI, 9%-99%). Their negative likelihood ratios ranged from 0.87 (95% CI, 0.71%-1.06%) to 0.93 (95% CI, 0.82%-1.07%); positive likelihood ratios were uninformative because of the small number of people with positive scores.
CONCLUSIONS: In low-risk populations, negative results from noninvasive scoring systems reliably exclude advanced fibrosis, without requirements for further tests. Positive test results are often a false-positive result and should prompt further testing.
Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Fatty Liver; Liver Fibrosis; Noninvasive Diagnosis; Sensitivity; Specificity

Mesh:

Year:  2017        PMID: 28286195     DOI: 10.1016/j.cgh.2017.02.031

Source DB:  PubMed          Journal:  Clin Gastroenterol Hepatol        ISSN: 1542-3565            Impact factor:   11.382


  13 in total

1.  Non-alcoholic fatty liver disease, liver fibrosis score and cognitive function in middle-aged adults: The Framingham Study.

Authors:  Galit Weinstein; Kendra Davis-Plourde; Jayandra J Himali; Shira Zelber-Sagi; Alexa S Beiser; Sudha Seshadri
Journal:  Liver Int       Date:  2019-06-26       Impact factor: 5.828

2.  Daily Aspirin Use Associated With Reduced Risk For Fibrosis Progression In Patients With Nonalcoholic Fatty Liver Disease.

Authors:  Tracey G Simon; Jacqueline Henson; Stephanie Osganian; Ricard Masia; Andrew T Chan; Raymond T Chung; Kathleen E Corey
Journal:  Clin Gastroenterol Hepatol       Date:  2019-05-09       Impact factor: 11.382

3.  Systematic screening for advanced liver fibrosis in patients with coronary artery disease: The CORONASH study.

Authors:  Thierry Thévenot; Sophie Vendeville; Delphine Weil; Linda Akkouche; Paul Calame; Clémence M Canivet; Claire Vanlemmens; Carine Richou; Jean-Paul Cervoni; Marie-France Seronde; Vincent Di Martino; Jérôme Boursier
Journal:  PLoS One       Date:  2022-05-26       Impact factor: 3.752

4.  Risk stratification of patients with nonalcoholic fatty liver disease using a case identification pathway in primary care: a cross-sectional study.

Authors:  Abdel Aziz Shaheen; Kiarash Riazi; Alexandra Medellin; Deepak Bhayana; Gilaad G Kaplan; Jason Jiang; Roy Park; Wendy Schaufert; Kelly W Burak; Monica Sargious; Mark G Swain
Journal:  CMAJ Open       Date:  2020-05-15

Review 5.  Nonalcoholic Fatty Liver Disease Among Individuals with HIV Mono-infection: A Growing Concern?

Authors:  Margaret Morrison; Heather Y Hughes; Susanna Naggie; Wing-Kin Syn
Journal:  Dig Dis Sci       Date:  2019-10-23       Impact factor: 3.199

Review 6.  Confounding factors of non-invasive tests for nonalcoholic fatty liver disease.

Authors:  Janae Wentong Wai; Charmaine Fu; Vincent Wai-Sun Wong
Journal:  J Gastroenterol       Date:  2020-05-25       Impact factor: 7.527

7.  Non-alcoholic fatty liver disease does not increase dementia risk although histology data might improve risk prediction.

Authors:  Ying Shang; Patrik Nasr; Mattias Ekstedt; Linnea Widman; Per Stål; Rolf Hultcrantz; Stergios Kechagias; Hannes Hagström
Journal:  JHEP Rep       Date:  2020-12-01

8.  Speculation of the Time-Dependent Change of FIB4 Index in Patients with Nonalcoholic Fatty Liver Disease: A Retrospective Study.

Authors:  Hiroshi Miyata; Satoru Miyata
Journal:  Can J Gastroenterol Hepatol       Date:  2018-03-12

9.  Current NAFLD guidelines for risk stratification in diabetic patients have poor diagnostic discrimination.

Authors:  Valentin Blank; David Petroff; Sebastian Beer; Albrecht Böhlig; Maria Heni; Thomas Berg; Yvonne Bausback; Arne Dietrich; Anke Tönjes; Marcus Hollenbach; Matthias Blüher; Volker Keim; Johannes Wiegand; Thomas Karlas
Journal:  Sci Rep       Date:  2020-10-27       Impact factor: 4.379

10.  Validation of a two-step approach combining serum biomarkers and liver stiffness measurement to predict advanced fibrosis.

Authors:  Hideki Fujii; Masaru Enomoto; Shinya Fukumoto; Tatsuo Kimura; Yuji Nadatani; Shingo Takashima; Atsushi Hagihara; Sawako Uchida-Kobayashi; Akihiro Tamori; Naoki Nishimoto; Norifumi Kawada
Journal:  JGH Open       Date:  2021-06-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.