Variability of lung function predicts loss of asthma control following withdrawal of inhaled corticosteroid treatment

Abstract

Background One aspect of a multidimensional approach to understanding asthma as a complex dynamic disease is to study how lung function varies with time. Variability measures of lung function have been shown to predict response to b 2 -agonist treatment. An investigation was conducted to determine whether mean, coefficient of variation (CV) or autocorrelation, a measure of short-term memory, of peak expiratory flow (PEF) could predict loss of asthma control following withdrawal of regular inhaled corticosteroid (ICS) treatment, using data from a previous study. Methods 87 adult patients with mild to moderate asthma who had been taking ICS at a constant dose for at least 6 months were monitored for 2e4 weeks. ICS was then withdrawn and monitoring continued until loss of control occurred as per predefined criteria. Twice-daily PEF was recorded during monitoring. Associations between loss of control and mean, CV and autocorrelation of morning PEF within 2 weeks pre-and post-ICS withdrawal were assessed using Cox regression analysis. Predictive utility was assessed using receiver operator characteristics. Results 53 out of 87 patients had sufficient PEF data over the required analysis period. The mean (389 vs 370 l/min, p<0.0001) and CV (4.5% vs 5.6%, p¼0.007) but not autocorrelation of PEF changed significantly from prewithdrawal to postwithdrawal in subjects who subsequently lost control, and were unaltered in those who did not. These changes were related to time to loss of control. CV was the most consistent predictor, with similar sensitivity and sensitivity to exhaled nitric oxide. Conclusion A simple, easy to obtain variability measure of daily lung function such as the CV may predict loss of asthma control within the first 2 weeks of ICS withdrawal.

Domiciliary diurnal variation of exhaled nitric oxide fraction for asthma control

“…In our study, we measured the fluctuation as the absolute variability irrespective of whether the level was higher or lower in any one direction. Frey and colleagues reported that the exponent of long-range fluctuation (a value) of FeNO and PEF predicted individual future risks of asthma exacerbation and reflected the current state of asthma control [6,17,35,40]. Our short-term analysis over only 2 weeks indicated that the diurnal fluctuation in FeNO was more related to asthma control than PEF was.…”

Monitoring asthma status

“…Authors noted that PEF readings are feasible and qualitatively appeared to track disease and symptoms, but symptom-based interventions may be more time and cost-effective. Monitoring changes in PEF as the mean, coefficient of variation, or autocorrelation and its predictive power for loss of asthma control following withdrawal of ICS was studied by Thamrin et al [32 ]. Mild to moderate asthma patients provided PEF data over a 6-week follow-up and found that mean and coefficient of variation of PEF changes were correlated to loss of control.…”

Systems Biology and Clinical Practice in Respiratory Medicine. The Twain Shall Meet

“…For many years, the diurnal variation in PEF has been recognized to be more severe in patients with greater symptoms of asthma and in those with more difficult to control, or brittle, asthma (56,57). Indeed, monitoring the variability in PEF within the first 2 weeks after withdrawal of inhaled corticosteroids may help predict loss of asthma control (58). Similarly, a drop in PEF combined with increased symptoms during a 1-week period have been shown to define a so-called "action point" beyond which a worsening of asthma will occur within the next 5 days (59).…”

“…We have already seen that fractal-type fluctuations of lung function over time may help to assess disease status and risk (58,60,62,65,72,77,78) and to monitor therapy success (58,60,79). Furthermore, in asthma, fluctuations in inflammatory markers such as fractional exhaled nitric oxide are related to symptoms (62,80), and the degree of concordance between the temporal changes in the biomarker and the temporal changes in daily symptoms may even serve as a measure of disease stability (62).…”