Published ahead of print on July 20, 2006, doi:10.1164/rccm.200512-1919OC
© 2006 American Thoracic Society doi: 10.1164/rccm.200512-1919OC
Classifying Severity of Cystic Fibrosis Lung Disease Using Longitudinal Pulmonary Function DataDepartments of Pediatrics and Genetics, Case Western Reserve University School of Medicine, Cleveland, Ohio; and Cystic FibrosisPulmonary Research and Treatment Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina Correspondence and requests for reprints should be addressed to Mark D. Schluchter, Ph.D., Department of Epidemiology and Biostatistics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 441064945. 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 patients with CF at the extremes of phenotype.
Methods: Results: Logistic regression of severity group on mixed model (empirical Bayes) estimates of intercept and slope of FEV1 (% pred) versus age discriminated better than did classification using FEV1 slope alone (ROC area = 0.995 vs. 0.821) and was equivalent to using estimated FEV1 at 20 yr of age as a single discriminator. The estimated survival percentile from a joint survival/longitudinal model provided equally good classification (ROC area = 0.994). Conclusions: In CF, estimated FEV1 (% pred) at 20 yr of age and the estimated survival percentile are useful indices of pulmonary disease severity.
Key Words: association studies FEV1 genetic modifiers This article has been cited by other articles:
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