Predicting future risk of asthma exacerbations using individual conditional probabilities.

BACKGROUND: Determination of future risk of exacerbations is a key issue in the management of asthma. We previously developed a method to calculate conditional probabilities (π) of future decreases in lung function by using the daily fluctuations in peak expiratory flow (PEF). OBJECTIVE: We aimed to extend calculation of π values to individual patients, validated by using electronically recorded data from 2 past clinical trials. METHODS: Twice-daily PEF data were analyzed from 78 patients with severe (study A) and 61 patients with poorly controlled (study B) asthma. For each patient, the π value was calculated from 5000 PEF data points simulated based on the correlation and distribution properties of observed PEF. Given an initial PEF, the π value was defined as the probability of a decrease in PEF to less than 80% of predicted value on 2 consecutive days within a month. These probabilities were then compared with actual occurrences of such events and clinically defined exacerbations within the following month. RESULTS: π Values were related to actual occurrences of decreases in PEF (adjusted R(2) > 0.800 for both studies). Every increase of 10% in π value was associated with an odds ratio of having a future exacerbation of 1.24 (95% CI, 1.07-1.43) for study A and 1.13 (95% CI, 1.02-1.26) for study B, with better sensitivity and specificity than clinic-measured FEV(1). CONCLUSION: These results from 2 independent datasets with differing asthmatic populations and differing exacerbation criteria provide support that clinically relevant quantification of individual future risk of exacerbations is possible.

Associations between fluctuations in lung function and asthma control in two populations with differing asthma severity.

BACKGROUND: Lung function is a major criterion used to assess asthma control. Fluctuation analyses can account for lung function history over time, and may provide an additional dimension to characterise control. The relationships between mean and fluctuations in lung function with asthma control, exacerbation and quality of life were studied in two independent data sets. METHODS: Data from 132 adults with mild to moderate asthma and 159 adults with severe asthma were analysed separately. Fluctuations in twice-daily peak expiratory flow (PEF) over 6 months were measured by α, representing the strength of correlation with past lung function and potentially asthma stability. α and mean percentage predicted PEF (%predPEF) were plotted with and compared between patients grouped by asthma control defined by recent GINA (Global Initiative for Asthma) guidelines, the Asthma Control Questionnaire score, exacerbations and Asthma Quality of Life Questionnaire score. Associations of α and %predPEF with these outcomes were examined using multiple regression analyses. RESULTS: Both α and %predPEF differed with and were significantly associated with GINA-defined asthma control in both the mild to moderate and severe asthma groups. Only α was related to whether or not exacerbations occurred in mild to moderate asthma, while %predPEF was more significantly related than α in severe asthma. In those with severe asthma, only %predPEF was significantly related to Asthma Control Questionnaire and Asthma Quality of Life Questionnaire scores. CONCLUSION: Lung function history quantified by fluctuation analysis provides additional information to mean lung function, and may help characterise the current state of asthma control. It may also potentially aid in phenotyping clinical asthma.