Quantifying Disease Severity Of Cystic Fibrosis Using Quantile Regression Methods

Kameryn Denaro,Douglas J Conrad,Barbara A Bailey

doi:10.6339/jds.202001_18(1).0008

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.

Highlights

Cystic fibrosis (CF) is a genetic disease that greatly decreases life expectancy and quality
This paper presents a new approach to describing disease severity of CF patients by using quantile regression rank scores and the corresponding normalized ranks
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

Summary

Introduction

Cystic fibrosis (CF) is a genetic disease that greatly decreases life expectancy and quality. CF is characterized by decreased mucociliary clearance, chronic polymicrobial infections which lead to airway wall remodeling. The hallmark of CF is chronic, progressive obstructive lung disease (Kulich et al, 2005). Among people with CF, the median predicted life expectancy for people born in the 2013-2017 US birth cohort is 44 years of age (CF National Registry, 2017). Lung function is a primary indicator of health for people with CF whether measured as Forced Expiratory Volume (FEV1), forced vital capacity (FVC), or FEV1 percent predicted. Two other measures of lung function are; (1) FVC, the volume of air that a patient is able to expire after full inspiration (2) FEV1 percent predicted, the percent of a nonsmoking population normalized for gender, height, age and ethnicity

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