Get started
Work

Turning subtypes into disease axes to improve prediction of COPD progression

Year: 2019
Type: article
Study design: Observational Study
Abstract: Chronic obstructive pulmonary disease (COPD) is an umbrella definition encompassing multiple disease processes. COPD heterogeneity has been described as distinct subgroups of individuals (subtypes) or as continuous measures of COPD variability (disease axes). There is little consensus on whether subtypes or disease axes are preferred, and the relative value of disease axes and subtypes for predicting COPD progression is unknown. Using a propensity score approach to learn disease axes from pairs of subtypes, we demonstrate that these disease axes predict prospective forced expiratory volume in 1 s decline and emphysema progression more accurately than the subtype pairs from which they were derived.
Source: Thorax
DOI: 10.1136/thoraxjnl-2018-213005
Authors: Junxiang Chen, Michael Cho, Edwin K Silverman, John E Hokanson, Greg L Kinney, James D Crapo, Stephen Rennard, Jennifer Dy, Peter Castaldi
Institutions: Northeastern University, Brigham and Women's Hospital, Colorado School of Public Health, University of Colorado Denver, National Jewish Health, AstraZeneca (United Kingdom), University of Nebraska Medical Center
Language: English
Field: Medicine
Open Access status: bronze
Awards: G2495236240, (2 of 2) Genetic Epidemiology of COPD, (2 of 2) Genetic Epidemiology of COPD, Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL, (1 of 2) Genetic Epidemiology of COPD, Genetics of Smoke-Altered LTA4H in COPD
OpenAlex ID: W2951964091
FWCI: 0.551
Cites: 9
Cited by: 7
Related to: 10