Abstract
A key measure of lung function in people with Cystic Fibrosis (CF) is Forced Expiratory Volume in the first second FEV(1) percent predicted (FEV(1)pp). This study aimed to address challenges in identifying predictors of FEV(1)pp, specifically dealing with non-linearity and the censoring effect of death. Data was obtained from a large multi-centre Australian Cystic Fibrosis Data Registry (ACFDR). A linear mixed model was used to study FEV(1)pp as the endpoint. There were 3655 patients (52.4% male) included in our study. Restricted cubic splines were used to fit the non-linear relationship between age of visit and FEV(1)pp. The following predictors were found to be significant in the multivariate model: age of patient at visit, BMI z-score, age interaction with lung transplantation, insulin dependent diabetes, cirrhosis/portal hypertension, pancreatic insufficiency, Pseudomonas aeruginosa infection and baseline variability in FEV(1)pp. Those with P. aeruginosa infection had a lower mean difference in FEV(1)pp of 4.7 units, p < 0.001 compared to those who did not have the infection. Joint modelling with mortality outcome did not materially affect our findings. These models will prove useful for to study the impact of CFTR modulator therapies on rate of change of lung function among patients with CF.