A Bayesian decision framework for F1–F2 MASLD follow-up under adherence uncertainty

Introduction Metabolic dysfunction-associated steatotic liver disease (MASLD) affects over one-third of the global population, yet follow-up frequency for patients with mild-to-moderate fibrosis (F1–F2) remains undefined. Variable adherence to lifestyle modification and to pharmacotherapies such as resmetirom and semaglutide further complicates management, risking both resource overuse and undetected disease progression. Methods We developed a Bayesian-informed expected net monetary benefit (NMB) decision framework comparing three strategies: aggressive follow-up (AF, visits every 6 months), conservative follow-up (CF, annual visits), and CF with mandatory between-visit Enhanced Liver Fibrosis testing (CF + ELF). Game theory concepts of adverse selection, moral hazard, and signaling motivated the model structure. Payoffs used published fibrosis transition probabilities, US EQ-5D-5L utilities, and Medicare costs at a willingness-to-pay threshold of $100,000/QALY. Adherence probability p was calibrated to therapy-specific proxy estimates. Sensitivity analyses varied the fibrosis improvement probability, the early-detection benefit of AF (0–75%), and the accountability effect of mandatory ELF (δ). Results AF was preferred over CF when p < 0.559, and CF + ELF was preferred over AF when p > 0.787. For lifestyle modification ( p = 0.30), AF was model-preferred. For semaglutide ( p = 0.835) and resmetirom ( p = 0.855), CF + ELF was model-preferred if mandatory ELF reduced non-adherent progression by at least 68% and 77%, respectively, and CF otherwise. CF was model-preferred in the intermediate zone (0.559 < p < 0.787), which is relevant to future therapies. Thresholds were invariant to the fibrosis improvement probability, and therapy-specific recommendations held when AF reduced non-adherent progression by approximately 31–63%. Patients weakly preferred AF on health outcome grounds, strictly so when non-adherent, suggesting that observed preferences for CF reflect burden. In a worked Bayesian example, two consecutive worsening ELF results lowered a resmetirom patient’s adherence probability from 0.855 to 0.506, making escalation to AF model-preferred. Discussion Follow-up intensity in F1–F2 MASLD may be better calibrated to treatment context and adherence probability than to uniform schedules. A hybrid approach combining patient signaling with physician oversight, informed by non-invasive testing and social determinants of health, offers an adaptable framework across lifestyle and pharmacological treatment settings. Prospective estimation of the early-detection benefit of AF and the accountability effect of mandatory ELF is needed before clinical implementation.