To the Editor:
Current asthma guidelines propose the use of quantitative composite measures of asthma control for assessment and follow-up 1. The use of inflammatory markers within the definition of control in asthma guidelines has been recently suggested 2. Sputum eosinophilia has been proposed as a useful surrogate marker of airway inflammation 3 but it is time-consuming and unfeasible in many clinical settings. In contrast, exhaled nitric oxide fraction (FeNO) is easily measured, well correlated with eosinophilic airway inflammation 4 and has been used in routine asthma care 5. However, to be included in the assessment of asthma control it should provide additional information. Factor analysis is a statistical method used to uncover which sets of variables form coherent subsets that are relatively independent of one another, and to obtain a small number of factors that account for most of the variance. We therefore aimed to assess the contribution of FeNO in the variability of asthma control using factor analysis.
We performed a cross-sectional study of 174 consecutive asthma patients (82% female, 70% atopic, 76% nonsmokers and 72% using inhaled steroids), with a mean±sd age of 40±15 yrs (table 1⇓). Patients were assessed using FeNO (NIOX®; Aerocrine, Solna, Sweden) measurements 6, forced expiratory volume in one second (FEV1; PIKO-1®; Ferraris, Hertford, UK) and the Asthma Control Questionnaire (ACQ) 7. A factor analysis using principal components as the method of extraction was conducted to explore the correlation between the following eight outcome measures: shortness of breath, morning symptoms, night-time symptoms, activity limitations, wheezing, use of bronchodilators, FEV1 % predicted and FeNO. Relationships between FeNO, FEV1 and ACQ were investigated using Pearson's correlation coefficients with a level of statistical significance set of p≤0.05. The study was approved by the Local Ethics Committee (Porto, Portugal) and informed consent was obtained.
The mean ACQ score was 1.22 (range 0.0–4.7), and 52% patients had well-controlled asthma (ACQ score <1.0).
Factor analysis yielded three factors that explained 77% of the variance: ACQ score (50%), FEV1 % pred (14%) and FeNO (13%; table 2⇓). No significant correlation between FeNO and ACQ score was observed, while FeNO and FEV1 had a weak but significant correlation (r = 0.243, p = 0.001).
Our data support the hypothesis that airway inflammation, clinical questions and lung function, addressed by FeNO and ACQ, are complementary for the evaluation of asthma status in adult patients. However, the cross-sectional nature of our study limits the interpretation of results, since exacerbations and other temporal variations could not be addressed. Nevertheless, this is the first study to quantitatively assess the contribution of FeNO and an asthma control measurement instrument for the variance of asthma status.
Although a few asthma studies have previously included inflammatory markers 8–10, none simultaneously reported factor analysis results on clinical variables, lung function and airway inflammation. Rosi et al. 8 identified three components in clinically stable asthmatics: airway function, airway responsiveness, and eosinophilic inflammation assessed using sputum analysis. In steroid-naïve asthma patients, the relationship between these parameters seems to be dependent on the duration of the disease 9. In the only study in which asthma symptoms were evaluated, weak correlations were observed in children between composite score of asthma severity, atopic parameters and FeNO 10.
In conclusion, clinical questions of the Asthma Control Questionnaire, forced expiratory volume in one second and exhaled nitric oxide fraction were grouped in distinct components, suggesting that they may complement each other in the assessment of asthma status. Further research, particularly observational longitudinal studies, should assess the usefulness of inflammatory biomarkers in conjunction with clinical questions and lung function parameters in asthma control assessment, and eventually establish an algorithm for treatment adjustment based on a thorough measure of asthma control.
Statement of interest
None declared.
Acknowledgments
The present authors would like to thank J. Ferraz de Oliveira (Immuno-allergology, Hospital of São João, Porto, Portugal) for help in study planning.
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