A Markov model of fibrosis development in nonalcoholic fatty liver disease predicts fibrosis progression in clinical cohorts

Author:

Knöchel Jane1,Bergenholm Linnéa2,Ibrahim Eman3ORCID,Kechagias Stergios4ORCID,Hansson Sara5,Liljeblad Mathias5ORCID,Nasr Patrik4,Carlsson Björn5ORCID,Ekstedt Mattias4,Ueckert Sebastian1ORCID

Affiliation:

1. Clinical Pharmacology and Quantitative Pharmacology Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca Gothenburg Sweden

2. DMPK, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden

3. Department of Pharmacy Uppsala University Uppsala Sweden

4. Department of Health, Medicine, and Caring Sciences Linköping University Linköping Sweden

5. Translational Science and Experimental Medicine, Research and Early Development Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca Gothenburg Sweden

Abstract

AbstractDisease progression in nonalcoholic steatohepatitis (NASH) is highly heterogenous and remains poorly understood. Fibrosis stage is currently the best predictor for development of end‐stage liver disease and mortality. Better understanding and quantifying the impact of factors affecting NASH and fibrosis is essential to inform a clinical study design. We developed a population Markov model to describe the transition probability between fibrosis stages and mortality using a unique clinical nonalcoholic fatty liver disease cohort with serial biopsies over 3 decades. We evaluated covariate effects on all model parameters and performed clinical trial simulations to predict the fibrosis progression rate for external clinical cohorts. All parameters were estimated with good precision. Age and diagnosis of type 2 diabetes (T2D) were found to be significant predictors in the model. Increase in hepatic steatosis between visits was the most important predictor for progression of fibrosis. Fibrosis progression rate (FPR) was twofold higher for fibrosis stages 0 and 1 (F0‐1) compared to fibrosis stage 2 and 3 (F2‐3). A twofold increase in FPR was observed for T2D. A two‐point steatosis worsening increased the FPR 11‐fold. Predicted fibrosis progression was in good agreement with data from external clinical cohorts. Our fibrosis progression model shows that patient selection, particularly initial fibrosis stage distribution, can significantly impact fibrosis progression and as such the window for assessing drug efficacy in clinical trials. Our work highlights the increase in hepatic steatosis as the most important factor in increasing FPR, emphasizing the importance of well‐defined lifestyle advise for reducing variability in NASH progression during clinical trials.

Publisher

Wiley

Subject

Pharmacology (medical),Modeling and Simulation

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