Development of a simple dynamic algorithm for individualized hepatocellular carcinoma risk-based surveillance using pre- and post-treatment general evaluation score.

Abstract

With the growing number of treated hepatitis C patients, the current 'one-size-fits-all' hepatocellular carcinoma (HCC) surveillance strategies for patients with advanced fibrosis represents a great burden on healthcare systems. An individualized HCC risk strategy incorporates the dynamic changes of HCC risk are lacking. This single-centre observational study included 3075 patients, with advanced fibrosis (≥F3) who achieved SVR following DAAs at Egyptian Liver research institute and hospital (ELRIAH) with follow-up period (range 6-72months). The performance of a recently developed General Evaluation Score (GES) HCC risk stratification score was calculated pre- and post-treatment using Harrell's c statistic. Times to HCC and cumulative incidences were calculated with Kaplan-Meier method and compared using log-rank (Mantel-Cox) test. Pre-treatment GES score stratified patients into low (60.4%), intermediate (23.4%), and (16.2%) high-risk score where 5-year cumulative incidences of HCC were 1.66%, 4.45% and 7.64%, respectively. Harrell's c statistic was 0.801. Post-treatment GES score stratified patients into low (57.4%), intermediate (30.7%) and (11.9%) high-risk score where 5-year cumulative incidences of HCC were 1.35%, 3.49% and 11.09% respectively. The cumulative HCC incidence increased significantly with higher scores (P < .001). Harrell's c statistic was 0.818. Using pre- and post-treatment GES score, GES algorithm was developed with higher predictive value. The cumulative HCC incidence increased significantly with higher scores (P < .001). Harrell's c statistic was 0.832. A dynamic algorithm incorporating both pre- and post-GES scores have better performance and predictive value compared with only pre-treatment assessments. The proposed algorithm would help to stratify those who need intensive or being excluded from screening.