A non-invasive algorithm accurately predicts advanced fibrosis in hepatitis C: A comparison using histology with internal–external validation☆

Background/Aims

Biochemical tests and ultrasonography (US) are useful in the non-invasive assessment of liver fibrosis in patients with chronic hepatitis C (CH–C); however histology remains the reference standard. This multicenter, cross-sectional cohort study evaluated the accuracy of APRI (AST-to-platelet-ratio-index) and liver surface ultrasound nodularity (LSN), singularly and sequentially combined in an algorithm, in diagnosing advanced fibrosis (i.e. METAVIR F3,F4), to derive a prediction rule to confirm or exclude F3,F4.

Methods

Four hundred and thirty consecutive CH–C patients with elevated ALT, grouped into a first cohort (training set), and an internal and an external validation cohort, were studied. APRI and LSN were compared to liver biopsy and sequentially combined in order to obtain a predictive rule for advanced fibrosis METAVIR F3,F4.

Results

LSN was negative and APRI⩽1 in 185/430 patients, whereas LSN was positive and APRI>2 in 46/430 cases, with a 94% diagnostic accuracy for presence/absence of F3, F4, respectively. In a further 60/430 patients, F3,F4 was detected with an accuracy of 83%. In the remaining cases no classification was possible.

Conclusions

An algorithm based on APRI and LSN confirms or excludes F3,F4 in 54% of CH–C patients with elevated ALT and suggests a highly probable diagnosis in a further one-sixth of patients, thus rendering liver biopsy unnecessary in these patients.

Abbreviations: US, ultrasonography, CH–C, chronic hepatitis C, APRI, AST-to-platelet-ratio-index, LSN, liver surface nodularity, ULN, upper limit of normal, ALT, alanine-aminotransferase, AST, aspartate-aminotransferase, HCV, hepatitis C virus, PLT, platelet count, INR, international normalized ratio, LR+ and LR−, positive and negative likelihood ratios, Sn, sensitivity, Sp, specificity, HCC, hepatocellular carcinoma, BMI, body mass index

Keywords: Chronic hepatitis C, Liver fibrosis, APRI score, Ultrasonography, Predictive algorithm