Background: Small airways dysfunction (SAD)is well recognised in asthma, yet its role in the severity and control of asthma is unclear. This study aimed to assess which combination of biomarkers, physiological tests, and imaging markers best measure the presence and extent of SAD in patients with asthma. Methods: In this baseline assessment of a multinational prospective cohort study (the Assessment of Small Airways Involvement in Asthma [ATLANTIS]study), we recruited participants with and without asthma (defined as Global Initiative for Asthma severity stages 1–5)from general practices, the databases of chest physicians, and advertisements at 29 centres across nine countries (Brazil, China, Germany, Italy, Spain, the Netherlands, the UK, the USA, and Canada). All participants were aged 18–65 years, and participants with asthma had received a clinical diagnosis of asthma more than 6 months ago that had been confirmed by a chest physician. This diagnosis required support by objective evidence at baseline or during the past 5 years, which could be: positive airway hyperresponsiveness to methacholine, positive reversibility (a change in FEV 1 ≥12% and ≥200 mL within 30 min)after treatment with 400 μg of salbutamol in a metered-dose inhaler with or without a spacer, variability in peak expiratory flow of more than 20% (measured over 7 days), or documented reversibility after a cycle (eg, 4 weeks)of maintenance anti-asthma treatment. The inclusion criteria also required that patients had stable asthma on any previous regular asthma treatment (including so-called rescue β2-agonists alone)at a stable dose for more than 8 weeks before baseline and had smoked for a maximum of 10 pack-years in their lifetime. Control group participants were recruited by advertisements; these participants were aged 18–65 years, had no respiratory symptoms compatible with asthma or chronic obstructive pulmonary disease, normal spirometry, and normal airways responsiveness, and had smoked for a maximum of 10 pack-years. We assessed all participants with spirometry, body plethysmography, impulse oscillometry, multiple breath nitrogen washout, CT (in selected participants), and questionnaires about asthma control, asthma-related quality of life (both in participants with asthma only), and health status. We applied structural equation modelling in participants with asthma to assess the contribution of all physiological and CT variables to SAD, from which we defined clinical SAD and CT SAD scores. We then classified patients with asthma into SAD groups with model-based clustering, and we compared asthma severity, control, and health-care use during the past year by SAD score and by SAD group. This trial is registered with ClinicalTrials.gov, number NCT02123667. Findings: Between June 30, 2014, and March 3, 2017, we recruited and evaluated 773 participants with asthma and 99 control participants. All physiological measures contributed to the clinical SAD model with the structural equation modelling analysis. The prevalence of SAD in asthma was dependent on the measure used; we found the lowest prevalence of SAD associated with acinar airway ventilation heterogeneity (S acin ), an outcome determined by multiple breath nitrogen washout that reflects ventilation heterogeneity in the most peripheral, pre-acinar or acinar airways. Impulse oscillometry and spirometry results, which were used to assess dysfunction of small-sized to mid-sized airways, contributed most to the clinical SAD score and differed between the two SAD groups. Participants in clinical SAD group 1 (n=452)had milder SAD than group 2 and comparable multiple breath nitrogen washout S acin to control participants. Participants in clinical SAD group 2 (n=312)had abnormal physiological SAD results relative to group 1, particularly their impulse oscillometry and spirometry measurements, and group 2 participants also had more severe asthma (with regard to asthma control, treatments, exacerbations, and quality of life)than group 1. Clinical SAD scores were higher (indicating more severe SAD)in group 2 than group 1, and we found that these scores were related to asthma control, severity, and exacerbations. We found no correlation between clinical SAD and CT SAD scores. Interpretation: SAD is a complex and silent signature of asthma that is likely to be directly or indirectly captured by combinations of physiological tests, such as spirometry, body plethysmography, impulse oscillometry, and multiple breath nitrogen washout. SAD is present across patients with all severities of asthma, but it is particularly prevalent in severe disease. The clinical classification of SAD into two groups (a milder and a more severe group)by use of impulse oscillometry and spirometry, which are easy to use, is meaningful given its association with GINA severity stages, asthma control, quality of life, and exacerbations. Funding: Chiesi Farmaceutici SpA.
ASJC Scopus subject areas
- Pulmonary and Respiratory Medicine