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

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.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.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.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.