Abstract
BACKGROUND: Nonalcoholic steatohepatitis (NASH) is a chronic liver disease associated with hepatic morbidity and mortality and extra-hepatic comorbidities. Published NASH cost-effectiveness models (CEMs) are heterogeneous and consistently omit comorbid conditions that frequently co-exist alongside NASH. We aimed to develop a de novo CEM framework that incorporates extra-hepatic disease states and outcomes alongside hepatic components to enable future estimation of the cost-effectiveness of NASH interventions. METHODS: Patient-level simulation and cohort-level Markov models were implemented in the same framework. Model inputs included fibrosis progression; late-stage liver disease outcomes; comorbidity outcomes for cardiovascular disease, type 2 diabetes, and obesity; mortality; health-related quality of life; and direct medical costs. The prototype analysis assessed the cost-effectiveness of obeticholic acid versus standard of care from a US payer perspective over a lifetime horizon with costs and effects discounted at 3% per annum. However, the CEM was designed for easy adaptation to other countries, time horizons, and other considerations. Efficacy and adverse event parameters were obtained from the 18-month interim analysis of the REGENERATE trial. Outputs include total and incremental costs, total life years, and quality-adjusted life years. RESULTS: In this model, total costs, total life years, and quality-adjusted life years were all higher with obeticholic acid compared with standard of care. Cross-validation of this model with the 2016 and 2020 Institute for Clinical and Economic Review models revealed marked differences, mainly driven by mortality inputs, transition probability estimates, and incorporation of the effect of treatment and comorbidities. CONCLUSION: This is the first CEM in NASH to incorporate the clinical consequences of several comorbidities. The flexible yet standardized framework permits estimation of the cost-effectiveness of NASH interventions in a variety of settings. The model currently includes several assumptions and will be further developed as more relevant data become available.