Development of risk scoring system for stratifying population for hepatocellular carcinoma screening

The age and risk level that warrants hepatocellular carcinoma (HCC) screening remains to be defined. To develop risk scores for stratifying average-risk population for mass HCC screening, we conducted a pooled analysis using data from three cohorts involving 12,377 Taiwanese adults 20-80 years of age. During 191,240.3 person-years of follow-up, 387 HCCs occurred. We derived risk scores from Cox's model in two thirds of participants and used another one third for model validation. Besides assessing discrimination and calibration, we performed decision curve analysis to translate findings into public health policy. A risk score according to age, sex, alanine aminotransferase, previous chronic liver disease, family history of HCC, and cumulative smoking had good discriminatory accuracy in both model derivation and validation sets (c-statistics for 3-, 5-, and 10-year risk prediction: 0.76-0.83). It also performed well across cohorts and diverse subgroups. Decision curve analyses revealed that use of the score in selecting persons for screening improved benefit at threshold probabilities of >2% 10-year risk, compared with current guidelines and a strategy of screening all hepatitis B carriers. Using 10-year risk 2% as a threshold for initiating screening, the screening age ranged from 20 to ≥60 years, depending on the tertile of risk scores and status of hepatitis B/C virus infection. Combining risk-score tertile levels and hepatitis virus status to stratify participants was more sensitive than current guidelines for HCC detection within 10 years (89.4% vs. 76.8%), especially for young-onset HCCs <50 years (79.4% vs. 40.6%), under slightly lower specificity (67.8% vs. 71.8%).

A simple HCC prediction algorithm was developed using accessible variables combined with hepatitis virus status, which allows selection of asymptomatic persons for priority of HCC screening.