Prediction rule using FeNO and symptoms for diagnosing asthma

16 May 2023

Background: Fractional exhaled nitric oxide (FeNO) is effective for ruling-in asthma, but its diagnostic value might be increased in combination with clinical signs and symptoms (CSS), also for ruling-out asthma. 

Aim: To create a diagnostic score incorporating FeNO and typical CSS for asthma in a hypothesis-based approach.

Design and Setting: Diagnostic multi-centre study, conducted in three practices of pneumologists in German ambulatory care. 

Methods: Reference standard was whole-body plethysmography, and bronchodilation test or bronchial provocation. Index test was FeNO measurement. CSS were evaluated with a questionnaire. Follow-up was performed after 3 months. An expert committee evaluated test results, symptoms, and course of disease for the final diagnosis. The outcome of a multiple logistic regression model was translated into a diagnostic score and internally validated by ten-fold cross validation.

Results: 308 patients were included. 186 (60.4%) were female, average age was 44.7 years and 161 (52.5%) had asthma.  The area under the curve of the diagnostic score was 0.747 (interquartile range 0.717-0.815). Allergic rhinitis, wheezing, dyspnea on exertion, coughing attacks at night, and awakening by shortness of breath were leading symptoms for ruling-in asthma. Frequent coughing and frequent respiratory infections were leading symptoms for ruling-out. The combination of FeNO and CSS allowed ruling-in asthma with a probability of up to 100%, and ruling-out with a post-test probability down to 10%.

Conclusion: The diagnostic scoring model increased the diagnostic value of FeNO in combination with CSS. The score allowed to rule-in asthma with high certainty, and to rule-out with acceptable certainty, respectively. 

Resource information

Respiratory conditions
  • Asthma
Respiratory topics
  • Diagnosis
Type of resource
Abstract
Conference
Munich 2023
Author(s)
Benjamin Valentin Brunn 1, Alexander Hapfelmeier 1, Rudolf J├Ârres 1, Konrad Schultz 1, Antonius Schneider 1 1 Technical University Munich, Munich, Germany