Use of clinical characteristics to predict spirometric classification of obstructive lung disease

Autor: Pascoe SJ, Wu W, Collison KA, Nelsen LM, Wurst KE, Lee LA
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: International Journal of COPD, Vol Volume 13, Pp 889-902 (2018)
Druh dokumentu: article
ISSN: 1178-2005
Popis: Steven J Pascoe,1 Wei Wu,2,3 Kathryn A Collison,1 Linda M Nelsen,4 Keele E Wurst,5 Laurie A Lee6 1Respiratory Medicines Development Center, GSK, Research Triangle Park, NC, USA; 2Biostatistics, PAREXEL International, Research Triangle Park, NC, USA; 3Clinical Statistics, GSK, Research Triangle Park, NC, USA; 4Value Evidence and Outcomes, GSK, Collegeville, PA, USA; 5Epidemiology, GSK, Collegeville, PA, USA; 6Research and Development, GSK, Stevenage, UK Background: There is no consensus on how to define patients with symptoms of asthma and chronic obstructive pulmonary disease (COPD). A diagnosis of asthma–COPD overlap (ACO) syndrome has been proposed, but its value is debated. This study (GSK Study 201703 [NCT02302417]) investigated the ability of statistical modeling approaches to define distinct disease groups in patients with obstructive lung disease (OLD) using medical history and spirometric data.Methods: Patients aged ≥18 years with diagnoses of asthma and/or COPD were categorized into three groups: 1) asthma (nonobstructive; reversible), 2) ACO (obstructive; reversible), and 3) COPD (obstructive; nonreversible). Obstruction was defined as a post-bronchodilator forced expiratory volume in 1 second (FEV1)/forced vital capacity
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