Glucagon-like Peptide-1 Receptor Agonists in Asthma Exacerbations: An Application of High-Dimensional Iterative Causal Forest to Identify Subgroups.
Journal:
Pharmacoepidemiology and drug safety
Published Date:
Aug 1, 2025
Abstract
BACKGROUND: Glucagon-like Peptide-1 Receptor Agonists (GLP1RA) may reduce asthma exacerbation (AE) risk, but it is unclear which populations benefit most. Recent pharmacoepidemiologic studies have employed iterative causal forest (iCF), a machine learning (ML) algorithm, to identify subgroups with heterogeneous treatment effects (HTEs). While iCF does not rely on prior knowledge of treatment-variable interactions, it may be constrained by missing or poorly defined variables in pharmacoepidemiologic studies.