Evidence map›Paper›PMID 29779083›Full record

ArticleDigestive diseases and sciences2018

Identifying Nonalcoholic Fatty Liver Disease Advanced Fibrosis in the Veterans Health Administration.

Yuval A Patel, Elizabeth J Gifford, Lisa M Glass, Marsha J Turner, Byungjoo Han, Cynthia A Moylan, Steve Choi, Ayako Suzuki, Dawn Provenzale, Christine M Hunt

Erratum issuedAbstract read
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In one paragraph

Article in Digestive diseases and sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  17. Population Management of Nonalcoholic Fatty Liver Disease.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2019
    Article
  18. Identifying and Treating Nonalcoholic Fatty Liver Disease.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2019
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Yuval A PatelDepartment of Medicine, Duke University Medical Center, Durham Veterans Administration Medical Center, Box 3913, Durham, NC, 27710, USA. Yuval.Patel@duke.edu.
Elizabeth J GiffordSanford School of Public Policy, Duke University, Durham, NC, USA.
Lisa M GlassDepartment of Medicine, University of Michigan, Ann Arbor, MI, USA.
Marsha J TurnerCooperative Studies Program Epidemiology Center, Durham Veterans Administration Medical Center, Durham, NC, USA.
Byungjoo HanCooperative Studies Program Epidemiology Center, Durham Veterans Administration Medical Center, Durham, NC, USA.
Cynthia A MoylanDepartment of Medicine, Duke University Medical Center, Durham Veterans Administration Medical Center, Box 3913, Durham, NC, 27710, USA.
Steve ChoiDepartment of Medicine, Duke University Medical Center, Durham Veterans Administration Medical Center, Box 3913, Durham, NC, 27710, USA.
Ayako SuzukiDepartment of Medicine, Duke University Medical Center, Durham Veterans Administration Medical Center, Box 3913, Durham, NC, 27710, USA.
Dawn ProvenzaleDepartment of Medicine, Duke University Medical Center, Durham Veterans Administration Medical Center, Box 3913, Durham, NC, 27710, USA.
Christine M HuntDepartment of Medicine, Duke University Medical Center, Durham Veterans Administration Medical Center, Box 3913, Durham, NC, 27710, USA.

Funding

Prediction and Prevention of Hepatic Decompensation in Patients with CirrhosisU01DK130177 · NIDDK · DUKE UNIVERSITY · PI MATTHEW R. KAPPUS, Cynthia A Moylan · 2021 to 2026
$2.0M
NIDDK NIH HHS U01 DK130177
6 · The paper itself

Abstract

backgroundNonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease. Severe NAFLD with advanced fibrosis results in substantial morbidity and mortality. Associated with metabolic syndrome, NAFLD is often initially clinically silent, yet intensive lifestyle intervention with 7% or greater weight loss can improve or resolve NAFLD. Using a Veterans Health Administration (VHA) liver biopsy cohort, we evaluated simple noninvasive fibrosis scoring systems to identify NAFLD with advanced fibrosis (or severe disease) to assist providers.

methodsIn our retrospective study of a national VHA sample of patients with biopsy-proven NAFLD or normal liver (2005-2015), we segregated patients by fibrosis stage (0-4). Non-NAFLD liver disease was excluded. We evaluated the diagnostic accuracy of the NAFLD fibrosis score (NFS), fibrosis-4 calculator (FIB-4), aspartate aminotransferase-to-alanine aminotransferase ratio (AST/ALT ratio), AST-to-platelet ratio index (APRI), and body mass index, AST/ALT ratio, and diabetes (BARD) score by age groups.

resultsWe included 329 patients with well-defined liver histology (296 NAFLD and 33 normal controls without fibrosis), in which 92 (28%) had advanced (stage 3-4) fibrosis. Across all age groups, NFS and FIB-4 best predicted advanced fibrosis (NFS with 0.676 threshold: AUROC 0.71-0.76, LR + 2.30-22.05, OR 6.00-39.58; FIB-4 with 2.67 threshold: AUROC of 0.62-0.80, LR + 4.70-27.45, OR 16.34-59.65).

conclusionsWhile NFS and FIB-4 scores exhibit good diagnostic accuracy, FIB-4 is optimal in identifying NAFLD advanced fibrosis in the VHA. Easily implemented as a point-of-care clinical test, FIB-4 can be useful in directing patients that are most likely to have advanced fibrosis to GI/hepatology consultation and follow-up.

Indexed as

Decision Support TechniquesUnited States Department of Veterans AffairsVeterans HealthAdolescentAdultAgedAlanine TransaminaseArea Under CurveAspartate AminotransferasesBiomarkersBiopsyBody Mass IndexClinical Enzyme TestsDatabases, FactualDiabetes MellitusFemaleAlanine TransaminaseAspartate AminotransferasesBiomarkersFatty liverFibrosisFibrosis prediction scoreNonalcoholic steatohepatitis

Identifiers

PMID29779083

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.