Bayesian Evidence Adaptive Treatment of Cystic Fibrosis

Antibiotics are a cornerstone of treatment, but most antibiotic regimens are only informed by old, underpowered, or poor-quality trials so no consensus exists on the treatment of pulmonary exacerbations (PEx) of CF. Across Australia, CF centres use a range of approaches and antibiotic regimens. Because preservation of lung function is important for extending life and quality of life, there is a need to determine the most effective empirical treatments of exacerbations. The aim of Bayesian Evidence Adaptive Treatment of Cystic Fibrosis (BEAT CF) is to optimise the management of CF by systematically evaluating the effectiveness of alternative treatment options, and by efficiently implementing these findings in routine care. The primary objective is to identify the effectiveness, or comparative effectiveness, of alternative interventions that are currently in routine use, or proposed for future use, in the management of acute pulmonary exacerbations in children and adults with CF, with respect to short-term improvements in lung function. BEAT CF is a prospective cohort. Those enrolled in the BEAT CF PEx Cohort consent solely to the systematic collection of their demographic, treatment, outcome (including safety), and other relevant clinical data to inform the future management of CF. Substudies of adults with a diagnosis of Cystic Fibrosis will be nested into the BEAT CF PEx Cohort. In the PEx Treatment Platform prescribed Interventions will be randomly assigned to participants who have consented to receiving randomised treatment. The Backbone Antibiotics Domain will be nested in the PEx Treatment Platform and Eligible participants in the Backbone Antibiotics Domain will be Assigned to one (and only one) Intervention in this Domain. The participant will be randomised (1:4) to either be Assigned to the Responsible Clinician's Selected Intervention for this Domain ('Clinician's Choice') or to a Randomly Assigned Intervention (Random Intervention).