Refining mild asthma phenotyping with FeNO: a population-based evaluation.

Area of Science:

• Pulmonology
• Allergy and Immunology
• Biomarkers in Respiratory Disease

Background:

• Asthma phenotyping is crucial for effective treatment strategies.
• Mild asthma classification requires precise differentiation of underlying inflammatory pathways.
• Current phenotyping models may benefit from incorporating additional biomarkers.

Purpose of the Study:

• To evaluate the utility of fractional exhaled nitric oxide (FeNO) in phenotyping mild asthma.
• To assess the combined value of FeNO and blood eosinophils in asthma classification.
• To compare the performance of an adapted ISAR-based model with and without FeNO.

Main Methods:

• Retrospective analysis of mild asthma patients.
• Inclusion of FeNO and blood eosinophil measurements.
• Application of an adapted Asthma-based Integrated Severity and Risk (ISAR) model.
• Evaluation of classification accuracy and predictive performance.

Main Results:

• Incorporating FeNO improved classification accuracy and calibration in the adapted ISAR model.
• The predictive improvement offered by FeNO was modest.
• FeNO's susceptibility to transient elevations was noted.
• Simplified algorithms showed potential for improved phenotyping in real-world settings.

Conclusions:

• FeNO has limited added value for routine clinical classification of mild asthma due to transient elevations.
• Blood eosinophils and FeNO together offer some improvement but may not be sufficient for all clinical scenarios.
• Simplified algorithms may be more practical and accurate for population-based asthma phenotyping under real-world constraints.