Noninvasive serum models to predict significant liver related events in chronic hepatitis C.

Aim: We aim to compare 20 noninvasive fibrosis scores (NIFS), derived from routine blood tests, for predicting significant liver-related adverse events (SLRE) in patients with chronic hepatitis C (CHC) after anti-viral treatment (AVT) with the goal to identify independent predictors for these outcomes.

Methods: From 1605 patients who received AVT (pegylated interferon and ribavirin) from January 2002 to June 2014, 20 NIFS were calculated from routine blood tests prior to AVT. Areas under the receiver-operating characteristic curve (AUROC) were calculated for each of these NIFS for predicting non-response to AVT and development of SLRE on follow-up.

Results: Mean age was 41.9 ± 9.7 years, and patients were predominantly genotype 4 (65%). After AVT, there were 1089 (67.8%) responders, 482 (30%) non-responders and 34 (2.1%) relapsers. After median follow-up of 6580.5 patient-years, 60 (3.8%) had SLRE, 52 (3.2%) had decompensation, and 11 (0.7%) had hepatocellular carcinoma (HCC). The predictive accuracy of NIFS and liver biopsy (LB) for non-response to AVT was low. FIB-4, FibroQ and King score showed high accuracy for predicting adverse events. For predicting decompensation, HCC and SLRE, FibroQ (0.881), King score (0.905) and FibroQ (0.877) had the highest AUROC, respectively. On multivariate analysis, independent predictors for treatment non-response (age, ALT, GGT, platelet count), HCC (albumin, GGT) and SLRE (albumin, GGT, platelet count) were identified.

Conclusions: Some simple pretreatment blood parameters and NIFS showed high accuracy for predicting development of SLRE post treatment. Application of these simple scores can improve assessment of long-term liver prognosis for CHC.