AI-Safe-C score: Assessing liver-related event risks in patients without cirrhosis after successful direct-acting antiviral treatment

Abstract

Background & Aims: Direct-acting antivirals (DAAs) have considerably improved chronic hepatitis C (HCV) treatment; however, follow-up after sustained virological response (SVR) typically neglects the risk of liver-related events (LREs). This study introduces and validates the artificial intelligence-safe score (AI-Safe-C score) to assess the risk of LREs in patients without cirrhosis after successful DAA treatment. Methods: The random survival forest model was trained to predict LREs in 913 patients without cirrhosis after SVR in Korea and was further tested in a combined cohort from Hong Kong and France (n = 1,264). The model's performance was assessed using Harrell's C-index and the area under the time-dependent receiver-operating characteristic curve (AUROC). Results: The AI-Safe-C score, which incorporated liver stiffness measurement (LSM), age, sex, and six other biochemical tests - with LSM being ranked as the most important among nine clinical features - demonstrated a C-index of 0.86 (95% CI 0.82-0.90) in predicting LREs in an external validation cohort. It achieved 3- and 5-year LRE AUROCs of 0.88 (95% CI 0.84-0.92) and 0.79 (95% CI 0.71-0.87), respectively, and for hepatocellular carcinoma, a C-index of 0.87 (95% CI 0.81-0.92) with 3- and 5-year AUROCs of 0.88 (95% CI 0.84-0.93) and 0.82 (95% CI 0.75-0.90), respectively. Using a cut-off of 0.7, the 5-year LRE rate within a high-risk group was between 3.2% and 6.2%, mirroring the incidence observed in individuals with advanced fibrosis, in stark contrast to the significantly lower incidence of 0.2% to 0.6% in a low-risk group. Conclusion: The AI-Safe-C score is a useful tool for identifying patients without cirrhosis who are at higher risk of developing LREs. The post-SVR LSM, as integrated within the AI-Safe-C score, plays a critical role in predicting future LREs. (c) 2024 European Association for the Study of the Liver. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.