A modeling platform for the comparative effectiveness and cost-effectiveness of HCC surveillance
The HCC Surveillance Simulator was developed to provide investigators with a platform to simulate virtual trials of HCC surveillance strategies in patients with cirrhosis. Its central aim is to characterize how blood-based and imaging biomarkers — individually or in combination — affect early-stage HCC detection, and to translate that detection into projected reductions in HCC mortality.
Equally important, the simulator is intended to inform the development of emerging modalities by establishing boundary and cutoff conditions: the minimum sensitivity and specificity, and the maximum cost, at which a candidate biomarker becomes cost-effective for routine surveillance. This addresses a recurring challenge for tests where incremental sensitivity is accompanied by additional false positives and downstream diagnostic burden, and where the optimal operating threshold cannot be chosen on accuracy alone but must be informed by cost-effectiveness.
Beyond evaluating single tests, the simulator is intended to support moving away from one-size-fits-all surveillance by helping distinguish patients in whom intensive screening yields net benefit from those in whom competing mortality or limited treatment eligibility makes aggressive screening low-value or potentially harmful through overdiagnosis. By making these trade-offs explicit, the tool is designed to serve as a shared platform for conducting virtual trials — enabling researchers to prioritize promising strategies for prospective study, guide resource allocation, and inform risk-stratified surveillance policy.
The simulator functions as a platform for in-silico evaluation of surveillance modalities prior to, or in parallel with, empirical study.
Estimate the minimum sensitivity and specificity, and maximum cost, at which a candidate blood or imaging biomarker is cost-effective — and locate the optimal operating point once added false positives and downstream imaging are accounted for.
Contrast established and emerging strategies on stage-specific detection, testing burden, lifetime cost, QALYs, and incremental cost-effectiveness ratios along the efficient frontier.
Examine how optimal strategy, screening interval, and willingness-to-pay interact with liver disease etiology and competing mortality, informing alternatives to one-size-fits-all surveillance.
Identify the most promising strategies and subgroups to advance to prospective study, and extrapolate observed surrogate endpoints to lifetime mortality and cost-effectiveness.
The model represents patients with compensated cirrhosis at baseline and generates population-level projections; results may not generalize to patients without cirrhosis, earlier fibrosis stages, or populations with materially different HCC risk, diagnostic access, treatment availability, or mortality. Several comparators and improved-adherence scenarios are exploratory model constructs rather than directly observed pathways. As with all decision-analytic analyses, projections depend on model structure and input quality, and lifetime extrapolation necessarily incorporates lower-certainty evidence. Outputs are intended for research, education, and policy exploration, and are not intended to guide individual clinical decisions.
