Risk Estimation for Hepatocellular Carcinoma in Chronic Hepatitis B (Reach -B): Development and Validation of a Predictive Score

Background Therapy for chronic hepatitis B reduces the risk of progressing to hepatocellular carcinoma (HCC); however, there is no suitable and accurate means to assess risk. This study aimed to develop and validate a simple scoring system to predict HCC risk in patients with chronic hepatitis B. Methods The development cohort consisted of 3584 patients without cirrhosis from the community-based Taiwanese REVEAL- HBV study (of whom 131 developed HCC during follow-up), and a validation cohort of 1505 patients from three hospitals in Hong Kong and South Korea (of whom 111 developed HCC during follow-up). We used Cox multivariate proportional hazards model to predict risk of HCC at 3,5, and 10 years. Variables included in the risk score were sex, age, serum alanine aminotransferase concentration, HBeAg status, and serum HBV DNA level. We calculated the area under receiver operating curve (AUROC) and calibration of predicted and observed HCC risk. Findings A 17-point risk score was developed, with HCC risk ranging from 0.0% to 23.6% at 3 years, 0.0% to 47 .4% at 5 years, and 0.0% to 81.6% at 10 years for patients with the lowest and highest HCC risk, respectively. AUROCs to predict risk were 0.811 (95 % CI 0-790-0.831) at 3 years, 0. 796 (0.775-0.816) at 5 years, and 0.769 ( 0.747-0.790) at 10 years in the validation cohort, and 0.902 (0.884-0.918) , 0. 783 (0.759-0.806), and 0.806 (0.783-0.828), respectively, after exclusion of 277 patients in the validation cohort with cirrhosis. Predicted risk was well calibrated with Kaplan-Meier observed HCC risk. Interpretation A simple-to- use risk score that uses baseline clinical variables was developed and validated. The score accurately estimates the risk of developing HCC at 3,5, and 10 years in patients with chronic hepatitis B. Clinicians can use this score to assess risk of HCC in patients with chronic hepatitis B and subsequently make evidence-based decisions about their clinical management