ArticlePharmacoepidemiology and drug safety2025
Glucagon-like Peptide-1 Receptor Agonists in Asthma Exacerbations: An Application of High-Dimensional Iterative Causal Forest to Identify Subgroups.
Article in Pharmacoepidemiology and drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Therapeutic Potential of Glucagon-like Peptide-1 Receptor Agonists in Respiratory Disorders.International journal of molecular sciences · 2026Review
- Glucagon-Like Peptide-1 Receptor Agonists vs Dipeptidyl Peptidase-4 Inhibitor Use on Risk of Asthma Exacerbation Among Diabetic Patients with Co-Morbid Asthma in Hong Kong.Journal of asthma and allergy · 2026Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundGlucagon-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.
methodsWe applied the high-dimensional iterative causal forest (hdiCF)-a causal ML algorithm requiring predefined variables-to MarketScan 2016-2020 claims data to identify populations with asthma that might benefit most from GLP1RA in reducing AE risk. We built a GLP1RA vs. sulfonylurea new-user cohort with ≥ 1 inpatient or two outpatient asthma encounters, excluding patients with nonasthma indications for systemic steroids. The outcome was acute AE (hospital admission or emergency department visit for asthma), assessed over 6 months using 599 high-dimensional features from inpatient/outpatient services and pharmacy claims.
resultsIn the overall population, GLP1RA decreased AE risk relative to sulfonylurea: aRD -1.4% (-2.0%, -0.8%). hdiCF identified three subgroups based on the quantity of systemic steroid prescription fills (0, 1, and ≥ 2): patients with ≥ 2 prescriptions (GLP1RA: 34 events/1367 individuals; sulfonylurea: 53/1013) benefited most from GLP1RA: aRD -3.8% (-5.3%, -2.2%).
conclusionsThis study demonstrates how automated feature identification can pinpoint clinically relevant subgroups with HTEs. The quantity of systemic steroid prescriptions, as a proxy for severe asthma, may guide personalized predictions of GLP1RA's short-term benefits on acute AE.
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