Patients with severe allergic rhinitis may encounter an elevated risk of developing asthma and other associated allergic conditions. It is known that “allergic rhinitis” and “allergic rhinitis + asthma” are two clinically distinct phenotypes of allergic rhinitis. Consequently, the aim of our study was to establish the diagnostic criteria for the progression of the allergic phenotype in children with seasonal allergic rhinitis (SAR). This cohort study included 47 patients aged between 6 to 17 years diagnosed with SAR, who were categorised into two groups: SAR/SAR with associated allergic conjunctivitis (AC) (Group 1), SAR with concomitant asthma/atopic dermatitis (Group 2). All participants underwent assessments to evaluate their Quality of Life (QoL), as well as the overall severity of nasal and non-nasal symptoms. Serum levels of Interleukin-33 (IL-33.) and STimulation expressed gene 2 (ST2) were quantified using enzyme immunoassay techniques. Additionally, the number of blood eosinophils, nasal eosinophils, Immunoglobulin E (IgE), and Secretory Immunoglobulin A (SIgA) were measured. Statistical analyses were conducted employing SPSS version 26.0 program. The diagnostic accuracy of the revised and simplified system was assessed using the receiver operating characteristic (ROC) curve. Throughout the study, we observed a significant reduction in the estimated total QoL score among children in both groups, with scores of 69.73 and 86.75 for the first and second groups, respectively, indicating a significant decrease decline in quality of life. A particularly critical criterion that exhibited a strong statistically significant correlation was the stress factor. Nearly 90% of patients in the second group, who are currently residing in conflict-affected areas, reported experiencing anxiety, which serves as a significant trigger for exacerbations. In our examination of the primary diagnostic criteria for the progression of SAR, we conducted a ROC analysis to assess the significance of predictors that may indicate an extreme allergic phenotype. These predictors included Visual Analogue Scale scores, blood eosinophil counts, nasal eosinophil levels, IgE, SIgA, IL-33, and ST2 levels. The analysis of potential prognostic factors allowed the creation of a practical algorithm for identifying patients at risk of developing an extreme allergic phenotype. This algorithm illustrates how our findings can be used to prognostically assess the severity of seasonal allergic rhinitis from a practical point of view. The conducted study identified the main diagnostic criteria that characterise the extreme allergic phenotype in children with SAR and determine the severity of its progression. Future research in this area will not only expand the existing diagnostic capabilities, but also contribute to the development of new treatment strategies for patients with allergic diseases.
Kryuchko et al. (2026) studied this question.