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

Clicks: 259
ID: 159248
2018
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Abstract
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 <0.7, and reversibility as a post-albuterol increase in FEV1 ≥200 mL and ≥12%. A primary model (PM), based on patients’ responses to a health care practitioner-administered questionnaire, was developed using multinomial logistic regression modeling. Other multivariate statistical analysis models for identifying asthma and COPD as distinct entities were developed and assessed using receiver operating characteristic (ROC) analysis. Partial least squares discriminant analysis (PLS-DA) assessed the degree of overlap between groups.Results: The PM predicted spirometric classifications with modest sensitivity. Other analysis models performed with high discrimination (area under the ROC curve: asthma model, 0.94; COPD model, 0.87). PLS-DA identified distinct phenotypic groups corresponding to asthma and COPD.Conclusion: Within the OLD spectrum, patients with asthma or COPD can be identified as two distinct groups with a high degree of precision. Patients outside these classifications do not constitute a homogeneous group. Keywords: asthma–COPD overlap syndrome, asthma, COPD, differential diagnosis, surveys and questionnaires
Reference Key
sj2018internationaluse Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Pascoe SJ;Wu W;Collison KA;Nelsen LM;Wurst KE;Lee LA
Journal tijdschrift voor geneeskunde
Year 2018
DOI
DOI not found
URL
https://www.dovepress.com/use-of-clinical-characteristics-to-predict-spirometric-classification--peer-reviewed-article-COPD
Keywords
asthma copd differential diagnosis

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