BACKGROUND: The criteria used to identify persons with asthma in epidemiologic studies are varying and, depending on the method used, can be challenging and resource consuming. OBJECTIVE: To develop a nomogram (scoring system) to identify adult patients with asthma using a combination of variables collected via a validated questionnaire. METHODS: We studied the first 268 women aged 40 to 69 years in the Shanghai Women's Asthma and Allergy Study who reported signs and symptoms of asthma and underwent either methacholine challenge testing or test of reversibility during the asthma screening survey between 2003 and 2007. These women were defined as having definite asthma (n=106) or not (n=162). Multivariable logistic regression analysis was performed to develop a predictive model for identifying asthma using survey information alone. RESULTS: Clinically relevant questions were used for the predictive multivariable logistic regression model and included the following: ever wheezing or whistling in the chest, current medication use for asthma, self-reported ever asthma, self-reported ever allergic rhinitis, family history of allergy, and age. The area under the receiver operating characteristic curve of the prediction model was 0.75 (95% confidence interval, 0.69-0.81). A nomogram was developed to assess the individual probability of asthma based on individually weighted variables in the predictive model. CONCLUSIONS: In clinical or epidemiologic studies, this asthma nomogram could be used as a tool to assess the probability of asthma for an individual patient by incorporating asthma-related predictor variables obtained through a field questionnaire.
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