Airway obstruction lability helps distinguish levels of disease activity in asthma

Modelling ASthma TrEatment Responses (MASTER): Effect of individual patient characteristics on the risk of exacerbation in moderate or severe asthma: A time-to-event analysis of randomized clinical trials

AIMS

There is limited understanding of how clinical and demographic characteristics are associated with exacerbation risk in patients with moderate-to-severe asthma, and how these factors correlate with symptom control and treatment response. Here we assess the relationship between baseline characteristics and exacerbation risk during regular dosing with inhaled corticosteroids (ICS) monotherapy or in combination with long-acting beta2-agonists (ICS/LABA) in clinical trial patients with varying levels of symptom control, as assessed by the asthma control questionnaire (ACQ-5).

METHODS

A time-to-event model was developed using pooled patient data (N = 16 282) from nine clinical studies [Correction added on 26 July 2023, after first online publication: The N value in the preceding sentence has been corrected in this version.]. A parametric hazard function was used to describe the time-to-first exacerbation. Covariate analysis included the assessment of the effect of seasonal variation, clinical and demographic baseline characteristics on baseline hazard. Predictive performance was evaluated by standard graphical and statistical methods.

RESULTS

An exponential hazard model best described the time-to-first exacerbation in moderate-to-severe asthma patients. Body mass index, smoking status, sex, ACQ-5, % predicted forced expiratory volume over 1 s (FEV1 p) and season were identified as statistically significant covariates affecting baseline hazard irrespective of ICS or ICS/LABA use. Fluticasone propionate/salmeterol (FP/SAL) combination therapy resulted in a significant reduction in the baseline hazard (30.8%) relative to FP monotherapy.

CONCLUSIONS

Interindividual differences at baseline and seasonal variation affect the exacerbation risk independently from drug treatment. Moreover, it appears that even when a comparable level of symptom control is achieved in a group of patients, each individual may have a different exacerbation risk, depending on their baseline characteristics and time of the year. These findings highlight the importance of personalized interventions in moderate-to-severe asthma patients.

Randomized Trial of Interventions to Improve Childhood Asthma in Homes with Wood-burning Stoves

BACKGROUND

Household air pollution due to biomass combustion for residential heating adversely affects vulnerable populations. Randomized controlled trials to improve indoor air quality in homes of children with asthma are limited, and no such studies have been conducted in homes using wood for heating.

OBJECTIVES

Our aims were to test the hypothesis that household-level interventions, specifically improved-technology wood-burning appliances or air-filtration devices, would improve health measures, in particular Pediatric Asthma Quality of Life Questionnaire (PAQLQ) scores, relative to placebo, among children living with asthma in homes with wood-burning stoves.

METHODS

A three-arm placebo-controlled randomized trial was conducted in homes with wood-burning stoves among children with asthma. Multiple preintervention and postintervention data included PAQLQ (primary outcome), peak expiratory flow (PEF) monitoring, diurnal peak flow variability (dPFV, an indicator of airway hyperreactivity) and indoor particulate matter (PM) PM2.5.

RESULTS

Relative to placebo, neither the air filter nor the woodstove intervention showed improvement in quality-of-life measures. Among the secondary outcomes, dPFV showed a 4.1 percentage point decrease in variability [95% confidence interval (CI)=-7.8 to -0.4] for air-filtration use in comparison with placebo. The air-filter intervention showed a 67% (95% CI: 50% to 77%) reduction in indoor PM2.5, but no change was observed with the improved-technology woodstove intervention.

CONCLUSIONS

Among children with asthma and chronic exposure to woodsmoke, an air-filter intervention that improved indoor air quality did not affect quality-of-life measures. Intent-to-treat analysis did show an improvement in the secondary measure of dPFV.

TRIAL REGISTRATION

ClincialTrials.gov NCT00807183. https://doi.org/10.1289/EHP849.

Identification of Asthma Subtypes Using Clustering Methodologies

Asthma is a heterogeneous disease comprising a number of subtypes which may be caused by different pathophysiologic mechanisms (sometimes referred to as endotypes) but may share similar observed characteristics (phenotypes). The use of unsupervised clustering in adult and paediatric populations has identified subtypes of asthma based on observable characteristics such as symptoms, lung function, atopy, eosinophilia, obesity, and age of onset. Here we describe different clustering methods and demonstrate their contributions to our understanding of the spectrum of asthma syndrome. Precise identification of asthma subtypes and their pathophysiological mechanisms may lead to stratification of patients, thus enabling more precise therapeutic and prevention approaches.

The asthma disease activity score: a discriminating, responsive measure predicts future asthma attacks

BACKGROUND

Classifying asthma severity or activity has evolved, but there are no published weighted composite measures of asthma disease activity that account for the relative importance of the many individual clinical variables that are widely used.

OBJECTIVES

We sought to develop a weighted and responsive measure of asthma disease activity.

METHODS

Discriminant and multiple regression analyses based on 2 previously conducted clinical trials were used to develop the Asthma Disease Activity Score (ADAS-6).

RESULTS

The ADAS-6 demonstrated content validity because its components assess different manifestations of asthma: FEV(1) (percent predicted), Asthma Quality of Life Questionnaire-Symptom domain, rescue β-agonist use, nocturnal awakenings, peak expiratory flow diurnal variability, and rescue β-agonist use diurnal variability. The ADAS-6 demonstrated cross-sectional and longitudinal validity. It was discriminating: it distinguished levels of disease activity and response to different treatment intensities (P < .0001). Similar results were obtained with an independent clinical trial. The ADAS-6 was highly responsive to treatment effects, with a standardized effect size exceeding that of other widely used outcome measures. Using ADAS-6 as the primary end point in the montelukast pivotal trials would have significantly reduced the sample size needed to detect a comparable change in outcome. Furthermore, increments in the ADAS-6 predicted the risk of future asthma attacks. A simplified Asthma Disease Activity Score 4-variable version (ADAS-4) demonstrated similar measurement properties.

CONCLUSIONS

The ADAS-6 and ADAS-4 are novel, weighted, and responsive measures of asthma disease activity. Use of these measures in clinical trials might better separate treatment effects, predict future asthma attacks, and substantially reduce sample size.