Clinical relevance of cluster analysis in phenotyping allergic rhinitis in a real-life study

Abstract

Background: Disease stratification, using phenotypic characterization performed either by hypothesis- or data-driven methods, was developed to improve clinical decisions. However, cluster analysis has not been used for allergic rhinitis.

Objective: To define clusters in allergic rhinitis and to compare them with ARIA (Allergic Rhinitis and Its Impact on Asthma), a hypothesis-driven approach.

Methods: A French observational prospective multicenter study (EVEIL: Echelle visuelle analogique dans la rhinite allergique) was carried out on 990 patients consulting general practitioners for allergic rhinitis and treated as per clinical practice. In this study, changes in symptom scores, visual analogue scales and quality of life were measured at baseline and after 14 days of treatment. A post hoc analysis was performed to identify clusters of patients with allergic rhinitis – using Ward's hierarchical method – and to define their clinical relevance at baseline and after 14 days of treatment. The cluster approach was compared to the ARIA approach.

Results: Patients were clustered into 4 phenotypes which partly followed the ARIA classes. These phenotypes differed in their disease severity including symptoms and quality of life. Physicians in real-life practice prescribed medication regardless of the phenotype and severity, with the exception of patients with ocular symptoms. Prescribed treatments were comparable in hypothesis- and data-driven analyses. The prevalence of uncontrolled patients during treatment was similar in the 4 clusters, but was significantly different according to the ARIA classes.

Conclusion: Cluster analysis using demographic and clinical parameters only does not appear to add relevant information for disease stratification in allergic rhinitis.