Lung Function Decline in Cystic Fibrosis: Impact of Data Availability and Modeling Strategies on Clinical Interpretations

Rhonda Szczesniak, Eleni-Rosalina Andrinopoulou, Weiji Su, Pedro M Afonso, Pierre-Régis Burgel, Elizabeth Cromwell, Emrah Gecili, Enas Ghulam, Christopher H Goss, Nicole Mayer-Hamblett, Ruth H Keogh, Theodore G Liou, Bruce Marshall, Wayne J Morgan, Joshua S Ostrenga, David J Pasta, Sanja Stanojevic, Claire Wainwright, Grace C Zhou, Gabriela FernandezAliza K Fink, Michael S Schechter

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)


Rationale: Studies estimating the rate of lung function decline in cystic fibrosis have been inconsistent regarding the methods used. How the methodology used impacts the validity of the results and comparability between studies is unknown. Objectives: The Cystic Fibrosis Foundation established a work group whose tasks were to examine the impact of differing approaches to estimating the rate of decline in lung function and to provide analysis guidelines. Methods: We used a natural history cohort of 35,252 individuals with cystic fibrosis aged >6 years in the Cystic Fibrosis Foundation Patient Registry (CFFPR), 2003–2016. Modeling strategies using linear and nonlinear forms of marginal and mixed-effects models, which have previously quantified the rate of forced expiratory volume in 1 second (FEV 1) decline (percent predicted per year), were evaluated under clinically relevant scenarios of available lung function data. Scenarios varied by sample size (overall CFFPR, medium-sized cohort of 3,000 subjects, and small-sized cohort of 150), data collection/reporting frequency (encounter, quarterly, and annual), inclusion of FEV 1 during pulmonary exacerbation, and follow-up length (,2 yr, 2–5 yr, entire duration). Results: Rate of FEV 1 decline estimates (percent predicted per year) differed between linear marginal and mixed-effects models; overall cohort estimates (95% confidence interval) were 1.26 (1.24–1.29) and 1.40 (1.38–1.42), respectively. Marginal models consistently estimated less rapid lung function decline than mixed-effects models across scenarios, except for short-term follow-up (both were ~1.4). Rate of decline estimates from nonlinear models diverged by age 30. Among mixed-effects models, nonlinear and stochastic terms fit best, except for short-term follow-up (,2 yr). Overall CFFPR analysis from a joint longitudinal-survival model implied that an increase in rate of decline of 1% predicted per year in FEV 1 was associated with a 1.52-fold (52%) increase in the hazard of death/lung transplant, but the results exhibited immortal cohort bias. Conclusions: Differences were as high as 0.5% predicted per year between rate of decline estimates, but we found estimates were robust to lung function data availability scenarios, except short-term follow-up and older age ranges. Inconsistencies among previous study results may be attributable to inherent differences in study design, inclusion criteria, or covariate adjustment. Results-based decision points reported herein will support researchers in selecting a strategy to model lung function decline most reflective of nuanced, study-specific goals.

Original languageEnglish
Pages (from-to)958-968
Number of pages11
JournalAnnals of the American Thoracic Society
Issue number7
Early online date8 Mar 2023
Publication statusPublished - 1 Jul 2023

Bibliographical note

Funding Information:
Supported by the Cystic Fibrosis Foundation grants GECILI20F0, LIOU14P0, LIOU14Y0, Naren19R0, and SZCZES18AB0; the National Heart, Lung, and Blood Institute grants R01HL141286 and R01HL125520; the Ben B. and Iris M. Margolis Foundation; and the Claudia Ruth Goodrich Stevens Endowment Fund.

Publisher Copyright:
Copyright © 2023 by the American Thoracic Society.


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