The LAC Score Indicates Significant Fibrosis in Patients With Chronic Drug-Induced Liver Injury: A Large Biopsy-Based...

Area of Science:

• Hepatology
• Biochemical Markers
• Diagnostic Algorithms

Background:

• Noninvasive methods for diagnosing fibrosis in chronic drug-induced liver injury (DILI) are currently lacking.
• Accurate fibrosis assessment is crucial for managing DILI and preventing disease progression.

Purpose of the Study:

• To develop and validate a novel noninvasive algorithm for diagnosing significant fibrosis in patients with chronic DILI.
• To improve diagnostic accuracy compared to existing noninvasive markers.

Main Methods:

• Retrospective analysis of biochemical and pathological data from 1,130 patients with biopsy-proven chronic DILI.
• Development of a noninvasive algorithm (LAC score) using multivariate logistic regression.
• Validation of the algorithm using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

Main Results:

• The novel LAC algorithm demonstrated a superior Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.81 for significant fibrosis.
• LAC performance (AUROC 0.81-0.90) surpassed individual markers like Liver Stiffness Measurement (LSM), Cholesterol Esterase (CHE), and AST to Platelet Ratio Index (APRI).
• Optimal cutoff values for LAC were identified for diagnosing advanced fibrosis and cirrhosis stages in both training and validation cohorts.

Conclusions:

• The LAC score is a promising noninvasive tool for accurately assessing significant fibrosis in chronic DILI.
• This algorithm can aid in identifying high-risk patients and establishing optimal treatment strategies.
• Further research may integrate LAC into clinical practice for improved DILI management.