Evidence map›Paper›PMID 39352015›Full record

ReviewJournal of clinical gastroenterology2025

Exploring Biomarkers in Nonalcoholic Fatty Liver Disease Among Individuals With Type 2 Diabetes Mellitus.

Fariba Ahmadizar, Zobair M Younossi

Abstract readReview
In one paragraph

Review in Journal of clinical gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

2 authors.

Fariba AhmadizarData Science and Biostatistics Department, Julius Global Health, University Medical Center Utrecht, Utrecht, The Netherlands.
Zobair M YounossiThe Global NASH Council, Center for Outcomes Research in Liver Disease, Washington, DC.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Integrating biomarkers into a comprehensive strategy is crucial for precise patient management, especially considering the significant healthcare costs associated with diseases. Current studies emphasize the urgent need for a paradigm shift in conceptualizing nonalcoholic fatty liver disease (NAFLD), now renamed metabolic dysfunction-associated steatotic liver disease (MASLD). Biomarkers are emerging as indispensable tools for accurate diagnosis, risk stratification, and monitoring disease progression. This review classifies biomarkers into conventional and novel categories, such as lipids, insulin resistance, hepatic function, and cutting-edge imaging/omics, and evaluates their potential to transform the approach to MASLD among individuals with type 2 diabetes mellitus (T2D). It focuses on the critical role of biomarkers in early MASLD detection, enhancing predictive accuracy, and discerning responses to interventions (pharmacological or lifestyle modifications). Amid this discussion, the complexities of the relationship between T2D and MASLD are explored, considering factors like age, gender, genetics, ethnicity, and socioeconomic background. Biomarkers enhance the effectiveness of interventions and support global initiatives to reduce the burden of MASLD, thereby improving public health outcomes. This review recognizes the promising potential of biomarkers for diagnostic precision while candidly addressing the challenges in implementing these advancements in clinical practice. The transformative role of biomarkers emerges as a central theme, promising to reshape our understanding of disease trajectories, prognosis, and the customization of personalized therapeutic strategies for improved patient outcomes. From a future perspective, identifying early-stage biomarkers, understanding environmental impact through exposomes, and applying a multiomics approach may reveal additional insight into MASLD development.

Indexed as

BiomarkersDiabetes Mellitus, Type 2Non-alcoholic Fatty Liver DiseaseDisease ProgressionHumansInsulin ResistanceBiomarkers

Identifiers

PMID39352015
PMCPMC11630663

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.