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

Area of Science:

• Hepatology
• Pharmacology
• Data Science

Background:

• Metabolic dysfunction-associated steatohepatitis (MASH) affects a large population, with limited approved treatments.
• Pioglitazone, a type 2 diabetes drug, is used off-label for MASH.
• There is a need for quantitative efficacy assessments of existing MASH therapies.

Purpose of the Study:

• To quantitatively assess pioglitazone's efficacy in improving MASH histological parameters and liver enzymes using a model-based meta-analysis.
• To develop predictive models for pioglitazone's effects on MASH.
• To establish a benchmark for evaluating novel MASH treatments.

Main Methods:

• A systematic literature search was conducted on PubMed and ClinicalTrials.gov.
• A model-based meta-analysis was performed, generating virtual data for histological outcomes and applying logistic, Weibull, and exponential models for data fitting.
• Model performance was evaluated using visual predictive checks, bootstrap methods, and stacked bar plots.

Main Results:

• Eight studies involving 540 patients were analyzed.
• Pioglitazone significantly improved steatosis, inflammation, ballooning, and fibrosis.
• Efficacy demonstrated dose- and time-dependent relationships for steatosis and ballooning, and linear relationships for inflammation and fibrosis. The Weibull model effectively described ALT and AST changes.

Conclusions:

• Pioglitazone demonstrates significant histological and biochemical improvements in MASH patients.
• The developed quantitative models provide a framework for assessing pioglitazone's effectiveness.
• These models can serve as a benchmark for evaluating new MASH-targeted therapies.