ABSTRACT
Cystic fibrosis is a genetic disease typically characterized by progressive lung damage and premature mortality. Pulmonary exacerbations, or flare-ups of the lung disease, often require hospitalization for intensive treatment. Approximately 25% of patients with cystic fibrosis do not recover their baseline lung function after pulmonary exacerbations. There is a relative paucity of evidence to inform treatment strategies for exacerbations. Compounding this lack of evidence, there are a large number of treatment options already as well as becoming available. This results in significant variability between medication regimens prescribed by different physicians, treatment centers and regions with potentially adverse impact to patients. The conventional strategy is to undertake essential randomized clinical trials to inform treatment decisions and improve outcomes for patients with exacerbations. However, over the past several decades, clinical trials have generally failed to provide information critical to improved treatment and management of exacerbations. Bayesian adaptive platform trials hold the promise of addressing clinical uncertainties and informing treatment. Using modeling and response adaptive randomization, they allow for the evaluation of multiple treatments across different management domains, and progressive improvement in patient outcomes throughout the course of the trial. Bayesian adaptive platform trials require substantial amounts of preparation. Basic preparation includes extensive stakeholder involvement including elicitation of consumer preferences and clinician understanding of the research topic, defining the research questions, determining the best outcome measures, delineating study sub-groups, in depth statistical modeling, designing end-to-end digital solutions seamlessly supporting clinicians, researchers and patients, constructing randomisation algorithms and importantly, defining pre-determined intra-study end-points. This review will discuss the motivation and necessary steps required to embark on a Bayesian adaptive platform trial to optimize medication regimens for the treatment of pulmonary exacerbations of cystic fibrosis.
ABSTRACT
BACKGROUND: The delivery of antipseudomonal antibiotics by inhalation to Pseudomonas aeruginosa-infected subjects with non-cystic fibrosis (CF) bronchiectasis is a logical extension of treatment strategies successfully developed in CF bronchiectasis. Dual release ciprofloxacin for inhalation (DRCFI) contains liposomal ciprofloxacin, formulated to optimise airway antibiotic delivery. METHODS: Phase II, 24-week Australian/New Zealand multicentre, randomised, double-blind, placebo-controlled trial in 42 adult bronchiectasis subjects with ≥2 pulmonary exacerbations in the prior 12 months and ciprofloxacin-sensitive P aeruginosa at screening. Subjects received DRCFI or placebo in three treatment cycles of 28 days on/28 days off. The primary outcome was change in sputum P aeruginosa bacterial density to the end of treatment cycle 1 (day 28), analysed by modified intention to treat (mITT). Key secondary outcomes included safety and time to first pulmonary exacerbation-after reaching the pulmonary exacerbation endpoint subjects discontinued study drug although remained in the study. RESULTS: DRCFI resulted in a mean (SD) 4.2 (3.7) log10 CFU/g reduction in P aeruginosa bacterial density at day 28 (vs -0.08 (3.8) with placebo, p=0.002). DRCFI treatment delayed time to first pulmonary exacerbation (median 134 vs 58 days, p=0.057 mITT, p=0.046 per protocol). DRCFI was well tolerated with a similar incidence of systemic adverse events to the placebo group, but fewer pulmonary adverse events. CONCLUSIONS: Once-daily inhaled DRCFI demonstrated potent antipseudomonal microbiological efficacy in adults with non-CF bronchiectasis and ciprofloxacin-sensitive P aeruginosa. In this modest-sized phase II study, DRCFI was also well tolerated and delayed time to first pulmonary exacerbation in the per protocol population.
