Evidence map›Paper›PMID 40785346›Full record

ArticleAlimentary pharmacology & therapeutics2025

MetALD: Diagnosis and Prognosis With Non-Invasive Tests.

Nikolaj Torp, Mads Israelsen, Stine Johansen, Georg Semmler, Camilla Dalby Hansen, Katrine Tholstrup Bech, Mette Lehmann Andersen, Katrine Holtz Thorhauge, Peter Andersen, Helle Lindholm Schnefeld and 10 more

Abstract read
In one paragraph

Article in Alimentary pharmacology & therapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  5. Review
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Nikolaj TorpDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.ORCID https://orcid.org/0000-0002-4378-6256
Mads IsraelsenDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.ORCID https://orcid.org/0000-0001-9443-5846
Stine JohansenDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.ORCID https://orcid.org/0000-0002-5031-2294
Georg SemmlerInstitute of Clinical Research, University of Southern Denmark, Odense, Denmark.
Camilla Dalby HansenDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Katrine Tholstrup BechDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Mette Lehmann AndersenDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Katrine Holtz ThorhaugeDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Peter AndersenDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Helle Lindholm SchnefeldDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Johanne Kragh HansenDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Ellen Lyngbeck JensenDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Emil Deleuran HansenDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Ida VillesenDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Katrine Prier LindvigDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Diana Julie LeemingNordic Bioscience, Herlev, Denmark.
Morten KarsdalNordic Bioscience, Herlev, Denmark.
Emmanuel A TsochatzisInstitute of Clinical Research, University of Southern Denmark, Odense, Denmark.ORCID https://orcid.org/0000-0001-5069-2461
Maja ThieleDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.
Aleksander KragDepartment of Gastroenterology and Hepatology, Centre for Liver Research, Odense University Hospital, Odense, Denmark.ORCID https://orcid.org/0000-0002-9598-4932

Funding

Horizon 2020 Framework Programme 668031Novo Nordisk Fonden 20OC0059393
6 · The paper itself

Abstract

backgroundNon-invasive tests (NITs) are central to diagnosing and stratifying risk in steatotic liver disease (SLD). However, it remains unclear whether guideline-recommended NIT cut-offs apply to metabolic and alcohol-related liver disease (MetALD).

aimEvaluate the diagnostic and prognostic performance of five NITs in patients with MetALD.

methodsSingle-centre study with 423 SLD patients, of whom 102 (24%) had MetALD. Patients were classified using histological or controlled attenuation parameter-defined hepatic steatosis and self-reported alcohol intake. We assessed the circulating markers of FIB-4, LiverRisk score, ELF and ADAPT together with transient elastography (TE) using established cut-offs for advanced fibrosis (≥ F3). Liver histology served as reference. Prognostic performance for hepatic decompensation and all-cause mortality was evaluated over a median follow-up of 62 months.

resultsAmong circulating NITs in MetALD, ELF and ADAPT both had the highest diagnostic accuracy (AUROC = 0.90), while it was lowest with LiverRisk score (AUROC = 0.74). The indeterminate zone between rule-out and rule-in cut-offs was largest for FIB-4 (34%). TE and circulating NIT concordance was highest for LiverRisk score (81%) to rule-out ≥ F3, and highest for ELF (88%) to rule-in ≥ F3. All included NITs predicted decompensation-free survival with their corresponding rule-out or rule-in cut-offs. A sequential 2-tier testing strategy (FIB-4 → TE) effectively stratified risk of decompensation. Incorporating a second-tier test (ELF or ADAPT) before TE reduced the number of TE referrals by 43% and 45%, without loss of prognostic performance.

conclusionWidely available NITs are applicable for MetALD, where cut-offs can be used to diagnose advanced fibrosis and predict clinical outcomes.

Indexed as

Fatty LiverAdultAgedBiomarkersElasticity Imaging TechniquesFemaleHumansLiver CirrhosisMaleMiddle AgedPrognosisBiomarkershepatic fibrosisliver disease managementprognostic biomarkersreferral pathwaysrisk stratification

Identifiers

PMID40785346
PMCPMC12543337

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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.