ReviewCurrent pharmaceutical design2026
Emerging Biomarkers for Early Detection and Prognosis of Liver Diseases.
Review in Current pharmaceutical design, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Integrative and interpretable machine learning framework for early non-invasive detection of clinically significant liver fibrosis.Frontiers in medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe purpose of this research is to review and evaluate both traditional and emerging biomarkers used in the diagnosis, monitoring, and treatment of liver diseases. The study aims to highlight how these biomarkers-such as liver enzymes, microRNAs, exosomes, and fibrosis-related proteins-can improve early detection, track disease progression, and support personalized treatment strategies for better patient outcomes. MATERIALS AND
methodsThis study uses a literature review to analyze both traditional (ALT, AST, ALP, bilirubin, etc.) and emerging biomarkers (microRNAs, exosomes, CRP, IL-6, MMPs, TIMPs) in liver disease. It focuses on their role in diagnosis, disease monitoring, and personalized treatment planning.
resultsTraditional biomarkers (ALT, AST, ALP, bilirubin, albumin) are key for liver function assessment. Emerging markers like microRNAs, exosomes, MMPs, and TIMPs improve early detection and disease monitoring. Together, they enhance diagnostic accuracy and support personalized treatment. DISCUSSION: The combination of traditional and novel biomarkers improves early detection, accurate diagnosis, and personalized treatment of liver diseases. New biomarkers, such as microRNAs and exosomes, offer higher sensitivity and specificity, enabling non-invasive diagnostics. The findings align with current research trends that promote the use of molecular and extracellular markers. These biomarkers provide deeper insights into liver disease mechanisms, particularly in fibrosis and hepatocellular carcinoma.
conclusionTraditional biomarkers are essential for liver assessment, while new ones like microRNAs, exosomes, MMPs, and TIMPs improve early diagnosis and monitoring. They support personalized care but need further validation for routine use.
Indexed as
Identifiers
41114480What OpenQuestion holds
Registered trials
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.