Abstract
Home-based measures of lung function, inflammation, symptoms, and medication use are frequently collected in respiratory clinical trials.
New statistical approaches are needed to make better use of the information contained in these data-rich variables.
One type of endpoint currently being evaluated for use in respiratory clinical trials is disease fluctuations.
In this work, we aimed to develop a model-based approach capable of describing several statistical properties of a patient’s daily PEF (peak expiratory flow) data.
We also investigate the association of these properties to exacerbation risk in moderate-to-severe asthmatics.