Model-Based Meta-Analysis of the Relationship Between Pioglitazone and Histological Outcomes in Metabolic Dysfunction-Associated Steatohepatitis Patients.

Abstract

Given the high prevalence of the population who have metabolic dysfunction-associated steatohepatitis (MASH), interest is growing in MASH-targeted treatments. However, currently, there has been only one regulatory approved drug for MASH (Rezdiffra). Pioglitazone, a commonly used type 2 diabetes mellitus drug, is currently used off-label for the treatment of MASH. Our study aimed to perform a model-based meta-analysis to quantitatively examine the efficacy of pioglitazone in improving histological parameters and liver enzymes in patients with MASH. A comprehensive search was performed in Pubmed and clinicaltrials.gov. We collected histological outcomes (including steatosis, inflammation, ballooning, and fibrosis) and liver enzyme data. Due to sparse data, the gathered histological outcomes were used to generate virtual data. Next, model development for the virtual histological dataset was performed using a logistic model. In addition, Weibull and exponential models were tested to find the best fit for liver enzyme data. Model evaluations were carried out by visual predictive check, bootstrap method, and stacked bar plot. Eight studies with 540 patients were included. A logit model was used to analyze four outcomes. The results showed that using pioglitazone improved all four histological parameters. These effects are dose- and time-dependent under the Emax-time model for steatosis and ballooning, and under the linear relationship for inflammation and fibrosis. For liver enzymes, the Weibull model fitted well for both ALT and AST data. In conclusion, the developed models of pioglitazone may serve as a benchmark to assess the effectiveness of novel MASH-targeted treatments.