Irene Mommers, Job F M van Boven, Jens H J Bos, Sumaira Mubarik, Eelko Hak, Maarten J Bijlsma
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引用次数: 0
Abstract
Purpose: 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.
期刊介绍：
Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment.
Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews.
Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews.
When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes.
The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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