Evaluation of De Ritis Ratio as a Predictive Biomarker for Liver Diseases

Abstract

Background: Liver diseases are a major cause of global morbidity and mortality, necessitating early detection and risk stratification. The De Ritis ratio (AST/ALT), first described by De Ritis et al. (1957), is a simple and non-invasive biomarker with diagnostic and prognostic value (1). Previous studies have demonstrated its utility in differentiating liver disease etiologies and predicting disease severity (2–6).

Objectives: To evaluate the De Ritis ratio as a predictive biomarker in liver diseases and to assess its diagnostic performance using correlation and ROC curve analysis.

Methods: A cross-sectional observational study was conducted on 45 patients with liver disease. Serum AST and ALT levels were measured, and the De Ritis ratio was calculated. Statistical analysis included descriptive statistics, Pearson correlation analysis, and Receiver Operating Characteristic (ROC) curve analysis to determine diagnostic accuracy.

Results: The majority of patients (53.3%) had a De Ritis ratio <1, suggestive of non-alcoholic fatty liver disease or viral hepatitis, while 13.3% had a ratio >2, indicative of alcoholic liver disease or advanced hepatic injury (3,6). The mean De Ritis ratio was 1.29 ± 1.35. Pearson correlation analysis demonstrated a moderate positive correlation between AST and ALT levels (r = 0.58, p < 0.001), indicating a significant association between the two enzymes. ROC curve analysis revealed good diagnostic performance, with an Area Under Curve (AUC) of approximately 0.84, supporting its ability to discriminate between mild and severe liver disease. These findings are consistent with earlier studies highlighting the prognostic role of the AST/ALT ratio in fibrosis and cirrhosis (2,4,10).

Conclusion: The De Ritis ratio is a simple, reliable, and cost-effective biomarker for liver disease evaluation. Integration of correlation and ROC analysis further strengthens its role in clinical assessment, prognosis, and risk stratification. It can be effectively utilized as a screening tool, particularly in resource-limited settings (5,7).