Scoring System and Clinical Application of COPD Diagnostic Questionnaires

• Published in: Chest Vol. 129; no. 6; pp. 1531 - 1539
• Main Authors: Price, David B., Tinkelman, David G., Nordyke, Robert J., Isonaka, Sharon, Halbert, R.J.
• Format: Journal Article
• Language: English
• Published: Northbrook, IL Elsevier Inc 01.06.2006; American College of Chest Physicians; Elsevier B.V
• Subjects: Adult; Age Factors; Aged; Asthma; Asthma - diagnosis; Biological and medical sciences; Cardiology. Vascular system; Chronic obstructive pulmonary disease, asthma; Diagnosis; Diagnosis, Differential; diagnostic techniques; Humans; Lung diseases; Lung diseases, Obstructive; Medical practices; Medical sciences; Middle Aged; obstructive lung diseases; Performance evaluation; Pneumology; Predictive Value of Tests; Primary care; Primary Health Care; Pulmonary Disease, Chronic Obstructive - diagnosis; Pulmonary Disease, Chronic Obstructive - etiology; Questionnaires; Regression analysis; Risk Factors; ROC Curve; sensitivity and specificity; Smoking; Smoking - adverse effects; Spirometry; Surveys and Questionnaires; United Kingdom; questionnaires; obstructive lung diseases; NPV; diagnostic techniques; PPV; ROC; primary care; sensitivity and specificity; Lung disease; Questionnaire; Respiratory disease; Evaluation scale; Cardiovascular disease; Care; Chronic; Sensitivity; Specificity; Primary; Bronchus disease; Obstructive pulmonary disease; Diagnosis; Technique; Medical application
• ISSN: 0012-3692; 1931-3543
• DOI: 10.1378/chest.129.6.1531

In most primary care settings, spirometric screening of all patients at risk is not practical. In prior work, we developed questionnaires to help identify COPD in two risk groups: (1) persons with a positive smoking history but no history of obstructive lung disease (case finding), and (2) patients with prior evidence of obstructive lung disease (differential diagnosis). For these questionnaires, we now present a scoring system for use in primary care. Scores for individual questions were based on the regression coefficients from logistic regression models using a spirometry-based diagnosis of obstruction as the reference outcome. Receiver operator characteristic analysis was used to determine performance characteristics for each questionnaire. Several simplified scoring systems were developed and tested. For both scenarios, we created a scoring system with two cut points intended to place subjects within one of three zones: persons with a high likelihood of having obstruction (high predictive value of a positive test result); persons with a low likelihood of obstruction (high predictive value of a negative test result); and an intermediate zone. Using these scoring systems, we achieved sensitivities of 54 to 82%, specificities of 58 to 88%, positive predictive values of 30 to 78%, and negative predictive values of 71 to 93%. These questionnaires can be used to help identify persons likely to have COPD among specific risk groups. The use of a simplified scoring system makes these tools beneficial in the primary care setting. Used in conjunction with spirometry, these tools can help improve the efficiency and accuracy of COPD diagnosis in primary care.