Internet-Based Monitoring in the Severe Asthma Research Program Identifies a Subgroup of Patients With Labile Asthma Control

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Abstract

Background

We designed an Internet-Based Monitoring Systems (IBS) survey to facilitate monitoring of asthma symptoms and asthma exacerbations in the Severe Asthma Research Program (SARP). Our objective was to evaluate compliance with the IBS survey tool and to explore how data from an IBS tool can inform understanding of asthma phenotypes.

Methods

We invited adult subjects in the SARP III cohort (N = 528) to complete a monthly IBS asthma control survey. We compared the characteristics of subjects who did and those who did not participate in the IBS survey tool. Among subjects who participated in the IBS (IBS+), we identified participants with low, medium, and high Asthma Control Test (ACT) score variability, and we explored asthma morbidity in these three participant subgroups.

Results

Two hundred fifty-nine subjects participated in the IBS (IBS+) survey. Compared with subjects who did not engage with the IBS (IBS–) survey, IBS+ subjects were older and more likely to be white, college educated, and have an annual household income > $25,000, and have controlled asthma. Among IBS+ participants, the subgroup with the highest ACT score variability was more likely to have severe asthma, with a lower ACT score at baseline and increased asthma-related health-care use (often precipitated by cold and flulike illnesses). Participants with high ACT variability were also characterized by metabolic dysfunction, as evidenced by obesity and hypertension.

Conclusions

Active participation with an Internet-based symptom survey tool in patients with severe asthma is influenced by race, socioeconomic status, and asthma control. Among survey participants, a group with highly variable (labile) asthma control is identifiable as a specific subgroup with unmet treatment needs. The association of asthma lability, increased susceptibility to adverse asthma effects of cold and flulike illnesses, and metabolic dysfunction provides clues for potentially effective intervention strategies.

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