Predictive performance and clinical utility of HCC risk scores in chronic hepatitis C: a comparative study

Background and aim Many HCC risk prediction scores were developed to guide HCC risk stratification and identify CHC patients who either need intensified surveillance or may not require screening. There is a need to compare different scores and their predictive performance in clinical practice. We aim to compare the newest HCC risk scores evaluating their discriminative ability, and clinical utility in a large cohort of CHC patients. Patients and methods The performance of the scores was evaluated in 3075 CHC patients who achieved SVR following DAAs using Log rank, Harrell’s c statistic, also tested for HCC-risk stratification and negative predictive values. Results HCC developed in 212 patients within 5 years follow-up. Twelve HCC risk scores were identified and displayed significant Log rank ( p ≤ 0.05) except Alonso-Lopez TE-HCC, and Chun scores ( p = 0.374, p = 0.053, respectively). Analysis of the remaining ten scores revealed that ADRES, GES pre-post treatment, GES algorithm and Watanabe (post-treatment) scores including dynamics of AFP, were clinically applicable and demonstrated good statistical performance; Log rank analysis < 0.001, Harrell’s C statistic (0.66–0.83) and high negative predictive values (94.38–97.65%). In these three scores, the 5 years cumulative IR in low risk groups be very low (0.54–1.6), so screening could be avoided safely in these patients. Conclusion ADRES, GES (pre- and post-treatment), GES algorithm and Watanabe (post-treatment) scores seem to offer acceptable HCC-risk predictability and clinical utility in CHC patients. The dynamics of AFP as a component of these scores may explain their high performance when compared to other scores.