Assessing Asthma Control with e-DASTHMA: A Data-Driven Approach


Investigators developed and validated a tool for daily assessment of asthma control that can be utilized in clinical trials as an endpoint.

Assessing Asthma Control with e-DASTHMA: A Data-Driven Approach

Bernardo Sousa-Pinto, MD, PhD

Current methods for assessing asthma rely on validated questionnaires, which provide a snapshot of asthma control over previous weeks. However, these questionnaires may not capture the daily fluctuations in symptoms that many asthma patients experience, according to a recent study.1

To address this limitation, investigators developed and validated an electronic daily asthma control score (e-DASTHMA) using the Mobile Airways Sentinel Network for airway diseases (MASK-air) app.

The tool offers several advantages over current methods, including the ability to capture these daily fluctuations in symptoms, which can guide treatment optimization. Additionally, the score can also be used as an endpoint in clinical trials, enabling more accurate assessments of treatment efficacy.

Reliable Asthma Control Scores

According to the analysis, investigators displayed high test-retest reliability and moderate-to-high responsiveness. The best-performing score displayed a strong correlation with the effect of asthma on work and school activities in an external validation cohort of patients with physician-diagnosed asthma (the INSPIRERS cohort).

The cohort also had good accuracy for the identification of patients with uncontrolled or partly controlled asthma based on the Global Initiative for Asthma (GINA) classification.

Bernardo Sousa-Pinto, MD, PhD, MEDicina da Comunidade, Informação e Decisão em Saúde, Department of Community Medicine, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, and investigators, used data from MASK-air, which is freely available to users in 27 countries, to develop and assess different daily control scores for asthma.

They included daily monitoring data from all MASK-air users aged 16-90 years who had used the app for at least 3 different calendar months and had reported at least 1 day of asthma medication use.

Developing a Daily Asthma Control Score

Data-driven control scores were developed based on asthma symptoms reported by a visual analogue scale and self-reported asthma medication use. The researchers evaluated more than 130k days of MASK-air data from 1662 users between May 2015-Dec 2021.

Findings showed that the e-DASTHMA scores were strongly correlated with visual analogue scale dyspnoea and moderately correlated with work comparators and quality-of-life-related comparators.

The team assessed the construct validity, test-retest reliability, responsiveness, and accuracy of each score using various factors, such as visual analogue scales on dyspnoea and work disturbance, EQ-5D-VAS, Control of Allergic Rhinitis and Asthma Test (CARAT), CARAT asthma, and Work Productivity and Activity Impairment: Allergy Specific (WPAI:AS) questionnaires.

Not only did the e-DASTHMA score provide a valuable tool for the daily assessment of asthma control, but it’s easily accessible through a smartphone app, which can facilitate patient self-monitoring and improve patient engagement in their asthma management, investigators noted.

The development and validation of the e-DASTHMA score is an important step towards improving the assessment and management of asthma. Further research is needed to assess the clinical utility of the e-DASTHMA score in various patient populations and settings.

“e-DASTHMA might help in the follow-up of patients with uncontrolled asthma, in shared decision making, and in the generation of daily alerts for patients or physicians,” investigators wrote. “Such a daily score avoids the recall biases associated with longer-term assessments, allowing for a better identification of exacerbations and their triggers.”


  1. Sousa-Pinto B, Jácome C, Pereira AM, et al. Development and validation of an electronic daily control score for asthma (e-DASTHMA): a real-world direct patient data study. The Lancet Digital Health. 2023;5(4):e227-e238.
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