Prospective Validation of Liver Cancer Risk Computation (LIRIC) Models

The investigators will conduct a prospective observational cohort study, separately deploying three separate LIRIC models (the general population, cirrhosis, and no_cirrhosis models) on retrospective de-identified EHR data of 44 HCOs in the USA, using the TriNetX federated network platform. LIRIC will generate a risk score for each individual. All risk-stratified individuals will be prospectively, electronically followed for up to 3-years to assess the primary end-point of HCC development. At the end of this period, model discrimination will be assessed, using the following metrics: AUROC, sensitivity, specificity, PPV/NPV. Risk scores generated by the model will be divided into quantiles. For each quantile, the investigators will evaluate the following: number of individuals in each quantile, number of HCC cases, PPV, NNS, SIR. Model calibration will be used for assessing the accuracy of estimates, based on the estimated to observed number of events. The model will dynamically re-evaluate all individual data every 6 months, re-classifying individuals (as needed).