Evaluating Clinical Effectiveness with CF Registries

Treatment and disease registries have played a vital role in understanding the heterogeneous nature of cystic fibrosis (CF) disease progression. The maturity of so many patient registries and recent national focus on their potential to improve patient-centered outcomes have led to the establishment of guidelines for the conduct of registry data analyses. Despite the insights garnered from utilizing CF patient registries, the analyses are plagued with methodological challenges, such as confounding, missing data, time varying treatment and/or covariates, and treatment-by-selection bias. Nonetheless, these registry studies have been essential for CF clinical effectiveness research. They reflect real-world clinical practice and allow for evaluating patient outcomes in a realistic clinical environment. In this chapter, we reflect on these advancements in registries and study results broadly and specifically in CF. We identify the key statistical challenges with the analysis of CF registry data from start to finish, including design considerations, quality assurance, issues with selection bias, covariate effects, sample size justification and missing data. We describe how these approaches are implemented to answer clinical effectiveness questions and undertake an illustrative example on tobramycin effectiveness and lung function decline