Regular treatment with salmeterol and inhaled steroids for chronic asthma: serious adverse events

Epidemiological evidence has suggested a link between beta2-agonists and increased asthma mortality. There has been much debate about possible causal links for this association, and whether regular (daily) long-acting beta2-agonists are safe. This is an updated systematic review.

Fluctuation analysis of lung function as a predictor of long-term response to beta2-agonists

The response to beta(2)-agonists differs between asthmatics and has been linked to subsequent adverse events, even death. Possible determinants include beta(2)-adrenoceptor genotype at position 16, lung function and airway hyperresponsiveness. Fluctuation analysis provides a simple parameter alpha measuring the complex correlation properties of day-to-day peak expiratory flow. The present study investigated whether alpha predicts clinical response to beta(2)-agonist treatment, taking into account other conventional predictors. Analysis was performed on previously published twice-daily peak expiratory flow measurements in 66 asthmatic adults over three 6-month randomised order treatment periods: placebo, salbutamol and salmeterol. Multiple linear regression was used to determine the association between alpha during the placebo period and response to treatment (change in the number of days with symptoms), taking into account other predictors namely beta(2)-adrenoceptor genotype, lung function and its variability, and airway hyperresponsiveness. The current authors found that alpha measured during the placebo period considerably improved the prediction of response to salmeterol treatment, taking into account genotype, lung function or its variability, or airway hyperresponsiveness. The present study provides further evidence that response to beta(2)-agonists is related to the time correlation properties of lung function in asthma. The current authors conclude that fluctuation analysis of lung function offers a novel predictor to identify patients who may respond well or poorly to treatment.

Risk of severe asthma episodes predicted from fluctuation analysis of airway function

Asthma is an increasing health problem worldwide, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible. We analyse the time series of peak expiratory flows, a standard measurement of airway function that has been assessed twice daily in a large asthmatic population during a long-term crossover clinical trial. Here we introduce an approach to predict the risk of worsening airflow obstruction by calculating the conditional probability that, given the current airway condition, a severe obstruction will occur within 30 days. We find that, compared with a placebo, a regular long-acting bronchodilator (salmeterol) that is widely used to improve asthma control decreases the risk of airway obstruction. Unexpectedly, however, a regular short-acting beta2-agonist bronchodilator (albuterol) increases this risk. Furthermore, we find that the time series of peak expiratory flows show long-range correlations that change significantly with disease severity, approaching a random process with increased variability in the most severe cases. Using a nonlinear stochastic model, we show that both the increased variability and the loss of correlations augment the risk of unstable airway function. The characterization of fluctuations in airway function provides a quantitative basis for objective risk prediction of asthma episodes and for evaluating the effectiveness of therapy.