Introduction
Asthma is a chronic disease with a high prevalence which is characterized by chronic airway inflammation and variable expiratory airflow limitations. Apart from airway obstruction, the presence of airway hyperresponsiveness (AHR) is accepted as one of the important key factors in asthma pathogenesis(1), and severe AHR predicts asthma with a high sensitivity(2).
The diagnostic performances of various bronchoprovocation tests are under discussion, but the direct methacholine challenge (MCC) is still the most common method to detect and quantify AHR, and the response to methacholine correlates with the severity of AHR(3). There is evidence that the MCC has a quite low specificity compared to indirect bronchoprovocation tests(2). Thus, indirect tests are suggested as the best screening tool to detect asthma. However, in patients suffering from asthma-related symptoms without an obstructive pattern in spirometry and without a positive reaction to indirect bronchoprovocation, there is a diagnostic dilemma in reaching the correct diagnosis, particularly as the absence of AHR confirmed by a negative MCC is considered in this patient subgroup as the “gold standard” in being able to exclude the presence of asthma with reasonable certainty(4).
Although the MCC is accepted as a safe diagnostic tool, it is time consuming and could be exhausting for patients(4). The aim of this study was to identify the predictive factors which allow for a reliable identification of patients with a high probability of AHR who would thus benefit from a validation by the MCC. This can prevent the mental stress and even other aggravating effects induced by the performance of the MCC in a pediatric population when it might not be necessary. Therefore, we have developed a prediction model combining factors that best predict AHR and can be easily obtained in practice. The diagnostic performance of this novel prediction model was also investigated.