Noninvasive Tests for Predicting Decompensation in Compensated Advanced Chronic Liver Disease: A Comprehensive...

Area of Science:

• Hepatology
• Diagnostic Medicine
• Biomarker Discovery

Background:

• Compensated advanced chronic liver disease (cACLD) requires accurate prognostication to guide patient care.
• Non-invasive tests (NITs) are crucial for predicting decompensation and liver-related outcomes in cACLD.
• Current NITs have limitations in accurately predicting individual patient risk.

Purpose of the Study:

• To comprehensively review studies evaluating the effectiveness of NITs in predicting decompensation or liver-related death in cACLD patients.
• To assess the performance of elastography and blood-based biomarkers.
• To identify innovative approaches for improving non-invasive risk prediction.

Main Methods:

• Systematic literature search of the PubMed database up to August 2025.
• Inclusion of prospective and retrospective studies on cACLD patients using NITs for outcome prediction.
• Separate analysis of elastography (specifically transient elastography-LSM) and blood-based tests (FIB-4, ELF, MELD).

Main Results:

• Higher liver stiffness measurement (LSM) values strongly correlate with increased decompensation risk, enabling risk stratification.
• Existing blood-based markers (FIB-4, ELF, MELD) show modest performance (AUC < 0.75) in predicting decompensation.
• Data calibration was lacking in most studies, hindering precise individual risk prediction.

Conclusions:

• NITs, particularly LSM, can stratify cACLD patients into low and high-risk groups for decompensation.
• Current NITs require improvement for accurate individual risk prediction.
• Future research should explore novel biomarkers (extracellular vesicles, genetic polymorphisms) and artificial intelligence for enhanced predictive models.