Rationale This study is part of a larger multi-method project to develop a questionnaire for identifying undiagnosed cases of chronic obstructive pulmonary disease (COPD) in primary care settings with specific interest in the detection of patients with moderate to severe airway Rabbit polyclonal to MET. obstruction or risk of exacerbation. COPD Foundation Peak Flow Study Cohort (N=5761) Burden of Obstructive Lung Disease (BOLD) Kentucky site (N=508) and COPDGene? (N=10 214 Four scenarios were examined to find the best smallest sets of variables that distinguished cases and controls:(1) moderate to severe COPD (forced expiratory volume in 1 second [FEV1] <50% predicted) versus no COPD; (2) undiagnosed versus diagnosed COPD; (3) COPD with and without exacerbation history; and (4) clinically significant COPD (FEV1<60% predicted or history of acute exacerbation) versus all others. Results From 4 to 8 variables were able to differentiate cases from controls with sensitivity ≥73 (range: 73–90) and specificity >68 (range: 68–93). Across scenarios the best models included age smoking status or history symptoms (cough wheeze phlegm) general or breathing-related activity limitation episodes of acute bronchitis and/or missed work days and non-work activities due to breathing or health. Conclusions Results provide insight into variables that should be considered during the development of candidate items for a new questionnaire to identify UK-383367 undiagnosed cases of clinically significant COPD. Keywords: COPD chronic airways obstruction primary care screening case identification data mining random forests INTRODUCTION A substantial number of individuals with chronic obstructive pulmonary disease (COPD) are undiagnosed.1 Although patients with mild COPD may benefit from treatment there is little empirical evidence to support this with the exception of smoking cessation which should be addressed with all smokers.2 As a result multiple organizations recommend against screening for asymptomatic COPD.2–5 It is well known however that people with moderate to severe airflow obstruction and those at risk for acute exacerbations experience significant health benefits from treatment including pharmacotherapy and UK-383367 rehabilitation.6 Identifying and treating these individuals should lead to better outcomes at the patient practice and population levels.7 Spirometry is the gold standard for confirmation of a COPD diagnosis3 and has been used to screen high-risk patients UK-383367 in pulmonary clinics.8 Rigorous administration of this test by trained personnel to all patients in primary care settings can be difficult and expensive with cost-effectiveness a concern when the yield may be 10% to 50% depending on the setting half of whom likely have mild disease.2 9 Questionnaire-based screening offers a practical method for identifying UK-383367 people who may have clinically significant COPD. Including peak expiratory flow (PEF) in the screening process could enhance efficiency by reducing the number of false positives. To date questionnaires have been designed to identify people with COPD (forced expiratory volume in one second [FEV1]/forced vital capacity [FVC] ratio <0.70) without reference to disease severity or exacerbation risk.15–22 The ability UK-383367 of these tools to detect cases have been modest 2 with sensitivity/specificity ranging 66% / 54% for an 8-item diagnostic questionnaire tested in the general population23 to 87% / 71% for a 6-item questionnaire in primary care 15 the latter associated with a positive predictive value (PPV) of 38% and a negative predictive value (NPV) of 97%. Nelson et al24 tested a three-staged approach (questionnaire PEF and spirometry) for identifying moderate to severe COPD (FEV1<60% predicted) in the general population. Six percent of 3791 participants (n=227) with 2 or more risk factors had abnormal PEF values suggesting a more sensitive screening questionnaire is needed to find the more severe cases. The current study UK-383367 was part of a larger multi-method project to develop a practical and effective primary care strategy for identifying undiagnosed patients with clinically significant COPD defined as an FEV1 % predicted < 60% or at risk of developing acute exacerbations. The project began with a comprehensive literature review of screening questionnaires and epidemiological studies of risk factors for acute exacerbations of COPD to identify candidate constructs for.