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Abstract

Predicting clinical outcomes in patients with chronic hepatitis C is challenging. We used the hepatitis C long-term treatment against cirrhosis (HALT-C) trial database to develop two models, using baseline values of routinely available laboratory tests together with changes in these values during follow-up to predict clinical decompensation and liver-related death/liver transplant in patients with advanced hepatitis C. Patients randomized to no treatment and who had ≥2-year follow-up without a clinical outcome were included in the analysis. Four variables (platelet count, aspartate aminotransferase [AST]/alanine aminotransferase [ALT] ratio, total bilirubin, and albumin) with three categories of change (stable, mild, or severe) over 2 years were analyzed. Cumulative incidence of clinical outcome was determined by Kaplan-Meier analysis and Cox regression was used to evaluate predictors of clinical outcome. In all, 470 patients with 60 events were used to develop models to predict clinical decompensation. Baseline values of all four variables were predictive of decompensation. There was a general trend of increasing outcomes with more marked worsening of laboratory values over 2 years, particularly for patients with abnormal baseline values. A model that included baseline platelet count, AST/ALT ratio, bilirubin, and severe worsening of platelet count, bilirubin, and albumin was the best predictor of clinical decompensation. A total of 483 patients with 79 events were used to evaluate predictors of liver-related death or liver transplant. A model that included baseline platelet count and albumin as well as severe worsening of AST/ALT ratio and albumin was the best predictor of liver-related outcomes. Conclusion: Both the baseline value and the rapidity in change of the value of routine laboratory variables were shown to be important in predicting clinical outcomes in patients with advanced chronic hepatitis C. (HEPATOLOGY 2011;)