A NEWLY developed prognostic model predicts liver cancer risk in patients with hepatitis B without cirrhosis, identifying a nonlinear relationship between viral load and cancer risk. This contrasts with previous beliefs that liver cancer risk increases linearly with hepatitis B virus (HBV) levels, and that antiviral treatment, which rapidly reduces viral load, would lower the risk accordingly. Instead, researchers discovered the highest risk at a viral load of 1 million units, suggesting that treatment decisions should prioritize viral load as a key factor in cancer prevention.
The study aimed to create and validate a model for predicting hepatocellular carcinoma (HCC) risk in noncirrhotic patients with chronic hepatitis B (CHB) who did not have significant alanine aminotransferase (ALT) elevation. Conducted as a multinational cohort study, the model was developed using data from 6,949 patients from a Korean hospital-based cohort and validated in 7,429 patients from Taiwan, Korea, and Hong Kong. Over a median follow-up of 10.0 years in the derivation cohort and 12.2 years in the validation cohort, 435 and 467 cases of HCC were identified, respectively. The model found that baseline HBV DNA levels were the strongest predictor of HCC development, revealing a parabolic association where moderate viral loads (around 1 million units or 6 log10 IU/mL) had the highest cancer risk. Other significant factors in the model were age, sex, platelet count, ALT levels, and hepatitis B e antigen status. The model performed well in both cohorts, with c-statistics of 0.844 and 0.813, demonstrating strong predictive ability.
The results demonstrate that this new prognostic tool offers a more precise method for assessing liver cancer risk in patients with noncirrhotic CHB, particularly those not currently receiving antiviral treatment. Its use in clinical practice could simplify decision-making by focusing on viral load, supporting earlier intervention to reduce cancer risk. Future research should aim to validate the model across different populations, including those receiving antiviral therapy, to improve its applicability.
Reference
Kim GA et al. Viral Load-Based Prediction of Hepatocellular Carcinoma Risk in Noncirrhotic Patients With Chronic Hepatitis B : A Multinational Study for the Development and External Validation of a New Prognostic Model. Ann Intern Med. 2024;177(10):1308-1318.
