Refining the approach to Cystic Fibrosis Pulmonary Exacerbations – modelling data to improve assessment and predict etiology.

Cystic fibrosis (CF) is a rare hereditary condition where patients experience frequent chest illnesses (exacerbations), resulting in a decline in lung health and premature death. Typically, exacerbation symptoms include an increase in cough and phlegm, with an accompanying decline in lung function. Up to half of all persons with CF (PWCF) require at least one course of intravenous antibiotics to manage their exacerbations each year, but at least 25% will not recover to their original lung function after treatment. While it is clear that not all chest illnesses in PWCF occur due to bacterial infections, we are unable to identify other causes when diagnosing a patient. Consequently, PWCF receive antibiotics in almost all instances of chest illness, even when bacteria may not be the cause, exposing these patients to unnecessary harm. This study will involve analysis of blood and phlegm samples from >100 PWCF to identify clinical and molecular markers that can indicate the cause of an exacerbation. Through the use of sophisticated statistical techniques, we will then develop a tool that can be used to predict exacerbation cause and allow physicians to select treatments that are more specific, appropriate and beneficial for patients.