Evidence map›Paper›PMID 32066623›Full record

ReviewGut2020

Advances in non-invasive assessment of hepatic fibrosis.

Rohit Loomba, Leon A Adams

Open access · greenAbstract readReview
In one paragraph

Review in Gut, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 190 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
190citing papers in PubMed, 4 pooled it
26.8field-weighted citation impact, top 1% of its field
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

190 citing papers in PubMed, 4 syntheses or guidelines pooled it, 312 citations in OpenAlex.

  1. Pooled it
  2. Guideline
  3. Pooled it
  4. Guideline
  5. Trial
  6. Article
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Unifying and unique roles of non-coding RNA biomarkers in liver and heart fibrosis.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2026
    Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

130 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 2 countries.

Rohit LoombaNAFLD Research Center, Division of Gastroenterology and Epidemiology, University of California at San Diego, La Jolla, California, USA roloomba@ucsd.edu.ORCID 0000-0002-4845-9991
Leon A AdamsMedicine and Pharmacology, The University of Western Australia, Nedlands, Western Australia, Australia.ORCID 0000-0002-3968-7909
The University of Western Australia · AUUniversity of California San Diego · US

Funding

UC San Diego Clinical and Translational Research InstituteUL1TR001442 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S, HOGARTH, MICHAEL · 2015 to 2024
$88.3M
Yeast Genetics and Stress Response Genes-BiomedicalP42ES010337 · NIEHS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI TUKEY, ROBERT H · 2000 to 2022
$69.8M
San Diego Digestive Diseases Research CenterP30DK120515 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LARS ECKMANN, Bernd G. Schnabl · 2019 to 2026
$10.8M
QUS Technology for Diagnosis and Grading of Hepatic Steatosis in NAFLDR01DK106419 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LOOMBA, ROHIT, SIRLIN, CLAUDE B · 2015 to 2019
$3.4M
NCATS NIH HHS UL1 TR001442NIDDK NIH HHS P30 DK120515NIDDK NIH HHS R01 DK106419NIEHS NIH HHS P42 ES010337
6 · The paper itself

Abstract

Liver fibrosis should be assessed in all individuals with chronic liver disease as it predicts the risk of future liver-related morbidity and thus need for treatment, monitoring and surveillance. Non-invasive fibrosis tests (NITs) overcome many limitations of liver biopsy and are now routinely incorporated into specialist clinical practice. Simple serum-based tests (eg, Fibrosis Score 4, non-alcoholic fatty liver disease Fibrosis Score) consist of readily available biochemical surrogates and clinical risk factors for liver fibrosis (eg, age and sex). These have been extensively validated across a spectrum of chronic liver diseases, however, tend to be less accurate than more 'complex' serum tests, which incorporate direct measures of fibrogenesis or fibrolysis (eg, hyaluronic acid, N-terminal propeptide of type three collagen). Elastography methods quantify liver stiffness as a marker of fibrosis and are more accurate than simple serum NITs, however, suffer increasing rates of unreliability with increasing obesity. MR elastography appears more accurate than sonographic elastography and is not significantly impacted by obesity but is costly with limited availability. NITs are valuable for excluding advanced fibrosis or cirrhosis, however, are not sufficiently predictive when used in isolation. Combining serum and elastography techniques increases diagnostic accuracy and can be used as screening and confirmatory tests, respectively. Unfortunately, NITs have not yet been demonstrated to accurately reflect fibrosis change in response to treatment, limiting their role in disease monitoring. However, recent studies have demonstrated lipidomic, proteomic and gut microbiome profiles as well as microRNA signatures to be promising techniques for fibrosis assessment in the future.

Indexed as

BiomarkersElasticity Imaging TechniquesHumansLiver CirrhosisMagnetic Resonance ImagingRisk AssessmentBiomarkerschronic liver diseasecirrhosiselastographyNonalcoholic fatty liver diseaseserum biomarkers

Identifiers

PMID32066623
PMCPMC7945956
OpenAlexW3006195986

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.