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Quantifying Disease Severity Of Cystic Fibrosis Using Quantile Regression Methods
Volume 18, Issue 1 (2020), pp. 148–160
Kameryn Denaro   Barbara A. Bailey   Douglas J. Conrad  

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https://doi.org/10.6339/JDS.202001_18(1).0008
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

This article presents a classification of disease severity for patients with cystic fibrosis (CF). CF is a genetic disease that dramatically decreases life expectancy and quality. The disease is characterized by polymicrobial infections which lead to lung remodeling and airway mucus plugging. In order to quantify disease severity of CF patients and compute a continuous severity index measure, quantile regression, rank scores, and corresponding normalized ranks are calculated for CF patients. Based on the rank scores calculated from the set of quantile regression models, a continuous severity index is computed for each CF patient and can be considered a robust estimate of CF disease severity.

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Keywords
Cystic Fibrosis FEV1 quantile regression robust regression

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