A simple prediction tool for inhaled corticosteroid response in asthmatic children

• Main Authors: Yi-Fan Wu, Ming-Wei Su, Bor-Luen Chiang, Yao-Hsu Yang, Ching-Hui Tsai, Yungling L. Lee
• Format: Article
• Language: English
• Published: BMC 2017-12-01
• Series: BMC Pulmonary Medicine
• Subjects: Childhood asthma; Inhaled corticosteroid; Drug response; Prediction model
• Online Access: http://link.springer.com/article/10.1186/s12890-017-0533-0

Abstract Background Inhaled corticosteroids are recommended as the first-line controller medication for childhood asthma owing to their multiple clinical benefits. However, heterogeneity in the response towards these drugs remains a significant clinical problem. Methods Children aged 5 to 18 years with mild to moderate persistent asthma were recruited into the Taiwanese Consortium of Childhood Asthma Study. Their responses to inhaled corticosteroids were assessed based on their improvements in the asthma control test and peak expiratory flow. The predictors of responsiveness were demographic and clinical features that were available in primary care settings. We have developed a prediction model using logistic regression and have simplified it to formulate a practical tool. We assessed its predictive performance using the area under the receiver operating characteristic curve. Results Of the 73 asthmatic children with baseline and follow-up outcome measurements for inhaled corticosteroids treatment, 24 (33%) were defined as non-responders. The tool we have developed consisted of three predictors yielding a total score between 0 and 5, which are comprised of the following parameters: the age at physician-diagnosis of asthma, sex, and exhaled nitric oxide. Sensitivity and specificity of the tool for prediction of inhaled corticosteroids non-responsiveness, for a score of 3, were 0.75 and 0.69, respectively. The areas under the receiver operating characteristic curve for the prediction tool was 0.763. Conclusions Our prediction tool represents a simple and low-cost method for predicting the response of inhaled corticosteroids treatment in asthmatic children.