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Predicting lung function decline in cystic fibrosis: the impact of initiating ivacaftor therapy

Respiratory Research(2024)

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Abstract
Modulator therapies that seek to correct the underlying defect in cystic fibrosis (CF) have revolutionized the clinical landscape. Given the heterogeneous nature of lung disease progression in the post-modulator era, there is a need to develop prediction models that are robust to modulator uptake. We conducted a retrospective longitudinal cohort study of the CF Foundation Patient Registry (N = 867 patients carrying the G551D mutation who were treated with ivacaftor from 2003 to 2018). The primary outcome was lung function (percent predicted forced expiratory volume in 1 s or FEV1pp). To characterize the association between ivacaftor initiation and lung function, we developed a dynamic prediction model through covariate selection of demographic and clinical characteristics. The ability of the selected model to predict a decline in lung function, clinically known as an FEV1-indicated exacerbation signal (FIES), was evaluated both at the population level and individual level. Based on the final model, the estimated improvement in FEV1pp after ivacaftor initiation was 4.89
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Key words
CFTR modulators,Cystic fibrosis,Lung function decline,Medical monitoring,Patient registry analysis,Prediction,Predictive probabilities,Rapid decline,Responsiveness,Trajectory
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