Background: Some patients with asthma demonstrate normal spirometry and remain undiagnosed without further testing. The objective of this study was to determine clinical predictors of asthma in symptomatic adults with normal spirometry.

Methods: Using random-digit dialing and population-based case-finding, we recruited adults from the community with respiratory symptoms and no previous history of lung disease. Participants with normal pre- and post-bronchodilator spirometry subsequently underwent bronchial challenge testing. Asthma was defined as a methacholine provocative concentration (PC20) of < 8 mg/mL. Univariate analyses identified predictive variables, which were then used to construct a multivariate logistic regression model to predict asthma. Model sensitivity, specificity, and area under the receiver operating curve (AUC) were calculated.

Results: Of 132 symptomatic individuals with normal spirometry, 26% had asthma. Univariate analyses demonstrated that 4 variables were predictive of asthma: female sex, FEV1 percentage predicted, Percentage Change in FEV1 post-bronchodilator, and answering 'yes' when asked about symptoms of cough, chest tightness, or wheezing provoked by exercise or cold air. The multivariate model yielded an AUC of 0.82 (95% CI 0.72-0.91), a sensitivity of 82%, and a specificity of 66%. 

Conclusions: Four readily available patient characteristics demonstrated high sensitivity and AUC for predicting undiagnosed asthma in adults with normal pre- and post-bronchodilator spirometry. These characteristics can help clinicians to decide which symptomatic individuals with normal spirometry should be investigated with bronchial challenge testing.