Published ahead of print on July 20, 2006, doi:10.1164/rccm.200512-1919OC Am. J. Respir. Crit. Care Med., Volume 174, Number 7, October 2006, 780-786 A more recent version of this article appeared on October 1, 2006
Submitted on December 16, 2005 Classifying Severity of Cystic Fibrosis Lung Disease Using Longitudinal Pulmonary Function DataMark D Schluchter1*,1 Department of Pediatrics, Case Western Reserve University School of Medicine, Cleveland, OH, USA, 2 Department of Pediatrics, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Department of Genetics, Case Western Reserve University School of Medicine, Cleveland, OH, USA, 3 Cystic Fibrosis - Pulmonary Research and Treatment Center, University of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, NC, USA * To whom correspondence should be addressed. E-mail: mds11{at}case.edu.
Rationale: The study of genetic modifiers in cystic fibrosis (CF) lung disease requires rigorous phenotyping. One type of genetic association study design compares polymorphisms in patients at extremes of phenotype, requiring accurate classification of pulmonary disease at varying ages.
Objective: To evaluate approaches to quantify severity of pulmonary disease, and their ability to discriminate between CF patients at the extremes of phenotype.
Methods: Key words: FEV1, Genetic Modifiers, Association studies
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F508 homozygotes (n=828) were initially classified as "severe" (approximate lowest quartile of FEV1 (% pred.) for age; 8-25 yrs) or "mild" disease (highest quartile of FEV1 for age; 
15 years). FEV1 measurements from the five years prior to enrollment (total=18,501 measurements; average 23 per subject) were analyzed with mixed models, and patient-specific estimates of FEV1 (% pred.) at ages 5, 10, 15, 20, and 25 yrs and slope of FEV1 versus age were examined for their ability to discriminate between groups using receiver operating characteristics (ROC) curve areas.
Results: Logistic regression of severity group on mixed model (empirical Bayes) estimates of intercept and slope of FEV1 (% pred.) vs. age discriminated better than did classification using FEV1 slope alone (ROC area = .995 vs. 821), and was equivalent to using estimated FEV1 at age 20 as a single discriminator. The estimated survival percentile from a joint survival/longitudinal model provided equally good classification (ROC area = .994).
Conclusions: In CF, estimated FEV1 (% pred.) at age 20 years and the estimated survival percentile are useful indices of pulmonary disease severity.
