Modelling Asthma Treatment Dynamics: Insights from the g-Formula
Irene Mommers,1 Job FM van Boven,2,3 Jens HJ Bos,1 Sumaira Mubarik,1 Eelko Hak,1 Maarten J Bijlsma1,4 1Pharmacotherapy, -Epidemiology and -Economics, University of Groningen, Groningen, The Netherlands; 2Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, G...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Dove Medical Press
2025-03-01
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| Series: | Clinical Epidemiology |
| Subjects: | |
| Online Access: | https://www.dovepress.com/modelling-asthma-treatment-dynamics-insights-from-the-g-formula-peer-reviewed-fulltext-article-CLEP |
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| Summary: | Irene Mommers,1 Job FM van Boven,2,3 Jens HJ Bos,1 Sumaira Mubarik,1 Eelko Hak,1 Maarten J Bijlsma1,4 1Pharmacotherapy, -Epidemiology and -Economics, University of Groningen, Groningen, The Netherlands; 2Groningen Research Institute for Asthma and COPD (GRIAC), University Medical Center Groningen, Groningen, The Netherlands; 3Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands; 4Laboratory of Population Health, Max Planck Institute for Demographic Research, Rostock, GermanyCorrespondence: Irene Mommers, Department of Pharmacotherapy, - Epidemiology and –Economics, University of Groningen, Antonius Deusinglaan 1, 9713 AV, Groningen, The Netherlands, Email i.mommers@rug.nlPurpose: The g-formula offers a promising approach to analyze long-term dynamic asthma treatment trajectories. This study investigates whether the g-formula can simulate real-world asthma treatment trajectories and predicts subgroup differences in switching behavior.Patients and Methods: This retrospective cohort study identified individuals aged 16- to 45 years who initiated inhaled asthma medication in the Netherlands between 1994 and 2021, from the IADB.nl pharmacy dispensing database. We used the g-formula combined with logistic regression to predict treatment trajectories and their associations with various patient characteristics, such as age, sex, chronic drug treatment for atopic diseases (ATD), cardiovascular diseases (CVD), thyroid diseases, arthritis, diabetes, gastroesophageal reflux disease (GERD), mental health problems (MHP), and immunosuppressants.Results: The simulations predicted 76% of individuals to switch treatment, on average 2.3 times, with the first switch occurring on average after 8.3 months, which agrees with the real-world observations (77%, 2.3 times and 7.9 months, respectively). Fewer 45-year-olds switched treatment compared to 16-year-olds (74% vs 78%, p < 0.001), but they switched earlier (8.1 vs 8.6 months, p < 0.001) and more frequently (2.4 vs 2.3 times, p < 0.001). Women were more likely to switch compared to men. Patients with ATD, CVD, MHP, or GERD switched significantly less often (p < 0.05).Conclusion: The g-formula effectively simulates asthma treatment trajectories and found higher age, male sex, ATD, CVD, MHP, and GERD to decrease overall switching behavior. These patients might benefit from earlier intervention or closer monitoring to reduce delays in treatment progression.Keywords: asthma, inhaled medication, treatment steps, trajectories, g-formula, prediction |
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| ISSN: | 1179-1349 |