The Natural History and Individualized Prediction of Liver Stiffness–Based Fibrosis Risk in MASLD

Background & Aims: Liver stiffness measurement (LSM) is a key tool for risk stratification in MASLD, yet static thresholds fail to capture dynamic transition across risk strata. We aimed to characterize LSM-risk transitions and develop a time-updated, individualized model for predicting state transitions, liver-related events and death (LREs/death). Method: In a real-world MASLD cohort, we applied a multi-state, time-homogeneous Markov model to quantify annual transition probabilities and mean state occupancy times across LSM-defined low-, intermediate-, and high-risk strata. A Markov model incorporating age, sex, type 2 diabetes (T2D), hypertension was used to generate individualized, time-updated risk trajectories and probabilities of LREs/death. Results: Among 11,514 MASLD individuals with ≥2 VCTE assessments, the low-risk category demonstrated notable stability, with 92% remaining unchanged at 1 year and a mean occupancy time of 8.43 years (95%CI:7.94-8.95). Contrarily the intermediate-risk category was highly dynamic, with only 39% remaining unchanged after 1 year and a mean occupancy time of 0.92 years (95%CI:0.88-0.96). T2D, hypertension, obesity substantially shorten low-risk occupancy time, whereas antidiabetic medication was associated with more favorable transitions. Finally, we developed a dynamic, multi-state Markov model (DYNAMO) integrating longitudinal LSM-defined risk states with relevant covariates to generate individualized predictions of state transitions and risks of LREs/death. Conclusions: LSM-based strata in MASLD represent distinct and meaningful dynamic trajectory. In particular, the marked instability of the intermediate-risk state supports more frequent reassessment. By quantifying transition pathways, and time-updated risks of LREs/death, this model may inform the personalized surveillance intervals and risk-adapted management.