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.