Knöchel J (1), Ibrahim Khalil E (2), Kechagias S (3), Ekstedt M (3), Bergenholm L (4)
1Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Gothenburg, Sweden, 2Pharmacometrics, Department of Pharmacy, Uppsala university, Sweden, 5Department of Health, Medicine, and Caring Sciences, Linköping University, Linköping, Sweden 4DMPK, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
Objectives: Non-alcoholic steatohepatitis (NASH), the more severe form of non-alcoholic fatty liver disease (NAFLD), is a major cause of liver-related morbidity and mortality world-wide for which no licensed therapy is currently available [1]. NASH is formally diagnosed with liver biopsy and graded histologically using the NAFLD activity score (NAS) including steatosis, lobular inflammation and hepatocyte ballooning defining disease activity, as well as stage of fibrosis development [2]. The disease progression is highly heterogenous and remains poorly understood. Currently, fibrosis stage is the best predictor for the development of end-stage liver disease and overall mortality [3-5]. Clinical trials for development of drugs to treat NASH need to show either improvement in fibrosis stage with no worsening in disease activity, or no worsening of fibrosis stage with improvement in disease activity. The aim of this work was to validate the performance of the Markov model to predict progression of fibrosis stage in NASH patients and investigate potential to use this model to guide future phase II and III designs in NAFLD/NASH.
Methods: In [6], a continuous-time Markov model was developed and parameterized using a longitudinal NAFLD cohort [7]. We use a refined version of this Markov model to perform two sets of clinical trial simulations. Firstly, we evaluated model performance to reproduce the fibrosis progression in the placebo groups of four published clinical trials. For this purpose, we designed 1,000 clinical cohorts mimicking the patient characteristics with respect to age, BMI, T2D, steatosis grade and fibrosis stage distribution for each trial. Average fibrosis progression in the simulated clinical trials was calculated and compared to data. Secondly, we used the Markov model to investigate fibrosis progression in four hypothetical patient cohorts with varying distribution in fibrosis stage, all with mean of fibrosis stage equal to two.
Results: First, we evaluated the performance of the model to predict fibrosis progression in four clinical trials. The four trials had comparable patient characteristics, but differing baseline fibrosis stage distributions. Overall, the model captured the observed changes in fibrosis stage. For two out of the four trials the model accurately predicted no change in fibrosis stage, while for the remaining two the model predicted a pronounced progression especially from stage 0 and 1 to stage 2. Secondly, we assessed the impact of initial fibrosis stage distribution at baseline on the observed change in fibrosis stage at the end of treatment.. The predicted mean change in fibrosis stage ranged from 0.03 to 0.07 which is in accordance with previous literature finding. The lowest increase was observed for trials including mainly fibrosis stage 2, which mimics the clinical situation best, as most of the current best practice non-invasive markers can establish fibrosis stage above 2 for a patient.
Conclusions: This work shows how this model could be used with the aim to optimise the baseline fibrosis stage in NASH trials, highlighting the utility of mathematical models to gain further understanding around disease progression and its impact on trial design and outcomes. Further on, incorporating also treatment effects into the Markov model have the potential to help in designing successful future Phase II studies for NASH patients.
References:
[1] Younossi, Z. M. The Epidemiology of Nonalcoholic Steatohepatitis. Clin. Liver Dis. 11, 92–94 (2018).
[2] Kleiner, D. E. et al. Design and Validation of a Histological Scoring System for Nonalcoholic Fatty Liver Disease. Hepatology 41, 1313–1321 (2005).
[3] Ekstedt, M. et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up. Hepatology 61, 1547–1554 (2015).
[4] Taylor, R. S. et al. Association Between Fibrosis Stage and Outcomes of Patients With Nonalcoholic Fatty Liver Disease: A Systematic Review and Meta-Analysis. Gastroenterology 158, 1611–1625 (2020).
[5] Angulo, P. et al. Liver Fibrosis, but no Other Histological Features, Associates with Long-term Outcomes of Patients With Nonalcoholic Fatty Liver Disease. Gastroenterology 149, 389–397 (2015).
[6] Ibrahim Khalil, E. et al Obesity and NAFLD activity score increase rate of fibrosis progression in a continuous-time Markov modelling of fibrosis progression in a long-term follow-up biopsy NAFLD cohort. PAGE meeting 2019
[7] Nasr, P., Ignatova, S., Kechagias, S. & Ekstedt, M. Natural history of nonalcoholic fatty liver disease: A prospective follow-up study with serial biopsies. Hepatol. Commun. 2, 199–210 (2018).
Reference: PAGE 29 (2021) Abstr 9736 [www.page-meeting.org/?abstract=9736]
Poster: Drug/Disease Modelling - Other Topics