Related Experiment Video
Updated: May 7, 2026
Assays for the Identification of Novel Antivirals against Bluetongue Virus
Published on: October 11, 2013
AI-Safe-C score: Assessing liver-related event risks in patients without cirrhosis after successful direct-acting
Huapeng Lin1, Terry Cheuk-Fung Yip2, Hye Won Lee3
1Department of Gastroenterology and Hepatology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Center for Digestive Diseases Research and Clinical Translation of Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Gut Microecology and Associated Major Diseases Research, Shanghai, China; Medical Data Analytics Center, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong.
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.
Impact And Implications:
The AI-Safe-C score introduces a paradigm shift in the management of patients without cirrhosis after direct-acting antiviral treatment, a cohort traditionally not included in routine surveillance protocols for liver-related events. By accurately identifying a subgroup at a comparably high risk of liver-related events, akin to those with advanced fibrosis, this predictive model facilitates a strategic reallocation of surveillance and clinical resources.
Related Concept Videos
01:28Esophageal Varices-II: Clinical Features and Management
In the initial assessment, a thorough review of the patient's medical history is vital to identify risk factors such as liver disease, alcohol abuse, or...
01:22Effect of Hepatic Disease on Pharmacokinetics: Pathophysiologic Assessment and Liver Function Test
01:08Effect of Hepatic Disease on Pharmacokinetics: Dose Adjustments Due to Hepatic Impairment
01:30Acute Kidney Injury IV: Diagnostic Studies and Prevention