Abstract
A key measure of lung function in people with Cystic Fibrosis (CF) is Forced Expiratory Volume in the first second FEV1 percent predicted (FEV1pp). This study aimed to address challenges in identifying predictors of FEV1pp, 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 FEV1pp 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 FEV1pp. 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 FEV1pp. Those with P. aeruginosa infection had a lower mean difference in FEV1pp 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.
Highlights
A key measure of lung function in people with Cystic Fibrosis (CF) is Forced Expiratory Volume in the first second FEV1 percent predicted (FEV1pp)
Current statistical models include generalised linear models (GLM)[5,6,7,8,9,10], generalised estimating equations (GEE)[11,12,13,14,15,16,17] and linear mixed models, which address the limitations mentioned above as well as allowing both fixed effect covariates and random intercepts to be modelled[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]
We found that a restricted cubic spline model for age of patient at visit with 3 knots fitted at ages 12, 18 and 30 provided a good fit to the model with the lowest Akaike information criterion (AIC) of 723,447 (Supplementary Information Table S1)
Summary
A key measure of lung function in people with Cystic Fibrosis (CF) is Forced Expiratory Volume in the first second FEV1 percent predicted (FEV1pp). There have been several attempts to study F EV1pp changes in people with CF using different methodologies and a recent review of articles has identified gaps and concluded that “further longitudinal studies are needed to develop statistical models to deal with nonlinear changes in lung function, quantify variability and the influence of risk factors. This should be undertaken without ignoring the censoring effect of death or lung transplantation”[4]. The main objective of our study was to provide a holistic F EV1pp modelling approach dealing with different slopes for before and after lung transplantation, handling death as an outcome and optimally dealing with the issue of non-linearity between FEV1pp and age of visit
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