Evidence mapPaperPMID 40485653Full record

ReviewTouchREVIEWS in endocrinology2025

The Use of Non-i nvasive Biomarkers to Screen for Advanced Fibrosis Associated with Metabolic Dysfunction-associated Steatotic Liver Disease in People with Type 2 Diabetes: A Narrative Review.

David M Williams, Jagadish Nagaraj, Jeffrey W Stephens, Thinzar Min

Abstract readReview
In one paragraph

Review in TouchREVIEWS in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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

2 citing papers in PubMed.

  1. Review
  2. Review
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

4 authors.

David M WilliamsDepartment of Diabetes and Endocrinology, Morriston Hospital, Swansea, UK.
Jagadish NagarajDepartment of Hepatology and Gastroenterology, Morriston Hospital, Swansea, UK.
Jeffrey W StephensDepartment of Diabetes and Endocrinology, Morriston Hospital, Swansea, UK.
Thinzar MinDiabetes Research Group, Swansea University Medical School, Swansea University, Swansea, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is growing interest in metabolic dysfunction-associated steatotic liver disease (MASLD), given its increasing prevalence and our developing understanding of the disease. People living with type 2 diabetes or obesity have a greater risk of developing significant hepatic steatosis and a greater risk of more rapid progression to steatohepatitis, advanced hepatic fibrosis and hepatocellular carcinoma. As such, various international bodies now advocate for routine screening for MASLD-related hepatic fibrosis in people with such risk factors. This would permit earlier targeted lifestyle interventions and the use of pharmacotherapies, which may reverse earlier stages of MASLD-associated fibrosis. This may improve both liver-related and cardiovascular outcomes in these higher-risk groups. Nonetheless, the identification of MASLD-related hepatic fibrosis is frequently limited to liver enzyme tests, given the lack of a systematic approach to investigation and screening. In this article, we discuss the potential to screen for advanced fibrosis in people with MASLD using various blood-based biomarkers, such as the Fibrosis-4 score, non-alcoholic fatty liver disease fibrosis score and enhanced liver fibrosis test, amongst other available patented and non-patented tests. We discuss the relative benefits and limitations of each and the potential for future research in this evolving area of clinical interest.

Indexed as

Liver diseaseliver fibrosismetabolic dysfunction-associated steatotic liver diseasemetabolic syndromescreeningsteatohepatitistype 2 diabetes

Identifiers

PMID40485653
PMCPMC12140637

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.