PT  - JOURNAL ARTICLE
AU  - Pascoe, Steven
AU  - Wu, Wei
AU  - Collison, Kathryn
AU  - Nelsen, Linda
AU  - Wurst, Keele
AU  - Lee, Laurie
TI  - Use of clinical characteristics to predict spirometric classification of obstructive lung disease
AID  - 10.1183/13993003.congress-2016.PA4185
DP  - 2016 Sep 01
TA  - European Respiratory Journal
PG  - PA4185
VI  - 48
IP  - suppl 60
4099  - http://erj.ersjournals.com/content/48/suppl_60/PA4185.short
4100  - http://erj.ersjournals.com/content/48/suppl_60/PA4185.full
SO  - Eur Respir J2016 Sep 01; 48
AB  - Introduction: Despite increased acceptance of asthma and COPD overlap, data on the relationship between clinical and spirometric features are limited.Aims and objectives: To quantify the relationship between patient-reportable facets of obstructive lung disease and spirometric classification of patients.Methods: Patients with asthma and/or COPD (n=1248) were divided into three groups: (i) asthma (non-obstructive {post-bronchodilator forced expiratory volume in 1 second/forced vital capacity ≥0.7} and reversible {response to salbutamol ≥200 mL and ≥12%}); (ii) asthma-COPD overlap syndrome (ACOS; obstructive and reversible); and (iii) COPD (obstructive and non-reversible).A questionnaire was created to record patient demographics, symptoms, morbidity and medical history. Multi-tier nominal logistic regression modelling identified discriminatory variables, which were assessed using model-based predictions relative to spirometry-based classification.Results: The modelled variables were consistent with ACOS in 369/530 patients with spirometry-classified ACOS, and consistent with no ACOS in 476/682 patients without spirometry-classified ACOS (Table). The model performed with 70% sensitivity and specificity (predictive values: negative 75%, positive 64%).Conclusions: Selective clinical questioning has modest predictive value for spirometric classification of obstructive lung disease.Funding: GSK (NCT02302417; GSK study 201703).