Allergy
September 2, 2026 · via Europe PMC
Classification of Seasonal Allergic Rhinitis Patients by Prospective Patient-Recorded Symptoms: The @IT.2020 Project.
Dramburg S, Hernandez Toro CJ, Grittner U, +53 more, Matricardi PM.
AI summary — for doctors, generated from the abstract only
In a multicenter study using daily electronic symptom diaries, many seasonal allergic rhinitis patients substantially over- or under-estimated their symptom frequency/severity when recalled retrospectively, and a new prospective classification approach identified distinct mild, moderate, and severe patient clusters.
What was studied
The @IT.2020 multicenter observational study recruiting 815 children and adults with seasonal allergic rhinitis (SAR) across 9 Mediterranean centers, comparing prospectively recorded daily symptom data (via e-Diary app, using RTSS and VAS scores) with retrospective ARIA classification administered at the start and end of pollen season, and using unsupervised clustering to generate a new prospective SAR classification.
Key findings
- 34.1% of patients (56/164) overestimated and 47.3% (173/366) underestimated the frequency of their symptoms when comparing retrospective reports to prospective e-Diary data.
- Only a moderate correlation was found between retrospectively reported SAR severity and prospectively recorded symptom severity.
- Unsupervised clustering identified distinct mild, moderate, and severe patient clusters based on prospective organ-specific (RTSS) and overall (VAS) symptom severity plus quality-of-life measures.
Clinical relevance
The findings suggest that retrospective patient recall (as used in the standard ARIA classification) may significantly misrepresent actual symptom burden in seasonal allergic rhinitis, and that prospective e-Diary-based classification could offer a more accurate way to evaluate and manage these patients, which may be relevant for clinicians assessing disease severity and treatment response.
Who should care
Limitations
This is an observational study without a formal comparator intervention, and the clustering approach, while identifying meaningful groups, requires further validation before being adopted as a standard classification tool in routine practice.
Patients with seasonal allergic rhinitis often misremember how often and how severely they experienced symptoms, and prospective daily symptom tracking may provide a more accurate way to classify disease severity.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Background
Seasonal allergic rhinitis (SAR) has been so far classified according to frequency and severity by retrospective information based on the ARIA (Allergic Rhinitis and its Impact on Asthma) classification. Electronic symptom diaries (e-Diaries) are feasible tools to collect prospective patient-reported data.
Objective
To test the consistency between prospectively recorded symptoms and retrospective ARIA classification and to generate a new SAR classification based on prospective e-Diary data.
Methods
Within the @IT.2020 multicentre observational study, we recruited 815 children and adults with SAR in nine study centres from Mediterranean countries. Participants recorded daily organ-specific (Rhinoconjunctivitis Total Symptom Score; RTSS) and general symptoms (visual analogue scale, VAS) plus quality-of-life measures via an e-Diary app. Retrospective clinical questionnaires were performed at the beginning (T0) and end (T1) of the pollen season. Unsupervised clustering analyses around medoids were implemented to classify SAR by prospective patient-reported data.
Results
One third (56/164, 34.1%) and almost half (173/366, 47.3%) of the patients retrospectively over- or underestimated the frequency of their symptoms, respectively. A moderate correlation was found between SAR severity reported at T1 and prospectively recorded symptom severity. An unsupervised clustering approach was able to identify distinct groups (mild, moderate, severe cluster) of patients based on the prospective severity of organ-specific (RTSS) and overall symptoms (VAS), as well as quality of life criteria.
Conclusions
A significant recall bias regarding frequency and severity of symptoms emerged by comparing the retrospective ARIA classification with prospectively recorded data by an e-Diary. A prospective approach to SAR classification, inspired by the retrospective ARIA classification, may facilitate a more precise evaluation of the patient for improved disease management.
DOI
10.1111/all.70447
PMID
42684055
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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