Daily digital biomarkers in the follow-up and clustering of patients with asthma.

Background And Research Question: We aimed to assess whether levels of digital biomarkers can reflect monthly patterns of asthma control.

Study Design And Methods: We performed a longitudinal study on patients with asthma and comorbid rhinitis who filled ≥26 days of data in a month in the MASK-air® app and who reported at least 1 day of treatment with an inhaled corticosteroid with or without a long-acting β-agonist (ICS ± LABA). We applied k-means cluster analysis to define clusters of months according to daily asthma control and medication use. Clusters were compared using digital biomarkers (visual analogue scale [VAS] on asthma symptoms and electronic daily asthma control score [e-DASTHMA]). We compared patients who did not switch with patients who switched their ICS ± LABA.

Results: We assessed 243 patients and 1358 months. We identified three clusters of poor asthma control despite high ICS ± LABA adherence, one cluster of poor asthma control and poor ICS ± LABA adherence, one cluster of good asthma control and high ICS ± LABA adherence and one cluster of good asthma control despite poor ICS ± LABA adherence. These clusters displayed relevant differences in VAS asthma and e-DASTHMA levels. Similar clusters were found in 'non-switchers' 'switchers'.

Conclusion: Levels of digital biomarkers reflect asthma control patterns and might be used to monitor patients with asthma.