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Background. Access to hepatitis C virus (HCV) treatment is limited in low- and middle-income countries (LMICs). Noninvasive biomarkers, such as fibrosis 4 (FIB-4) and aminotransferase to platelet ratio index (APRI), are low-cost alternatives to staging liver disease and identifying treatment need in people with chronic HCV infection, but their accuracy has not been evaluated in LMICs. Methods. We tested the accuracy of FIB-4 and APRI at validated cutoffs (FIB-4 <1.45, >3.25; APRI <0.5, >1.5) in predicting severe liver stiffness by elastography among 281 persons chronically infected with HCV. Multivariable logistic and Cox regression were used to identify markers of improved prediction and mortality, respectively. Results. Sensitivity and specificity of FIB-4 and APRI for predicting severe stiffness were 62% and 87% and 61% and 83%, respectively. Fibrosis 4 and APRI were less accurate in excluding significant stiffness; however, performance of models significantly improved with γ-glutamyl transpeptidase (GGT) and body mass index (BMI) (area under receiver operating characteristic curve, 0.81; 95% confidence interval, .76–.87). Severe liver stiffness predicted via FIB-4 >3.25, APRI >1.5, and a modified FIB-4 that included GGT and BMI were significantly associated with increased mortality. Conclusions. Fibrosis 4 and APRI may be useful in identifying individuals with severe stiffness who need treatment and continued monitoring in LMICs. Exclusion of significant stiffness may be improved by including GGT and BMI to FIB-4 models.

Serum Fibrosis Markers for the Diagnosis of Liver Disease Among People With Chronic Hepatitis C in Chennai, India