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Holzmann, C. ; Karg, J.* ; Reiger, M. ; Kharba, R. ; Romano, P. ; Scheiwein, S.* ; Khalfi, C. ; Muzalyova, A.* ; Brunner, J.O.* ; Hammel, G. ; Damialis, A.* ; Traidl-Hoffmann, C. ; Plaza, M.P. ; Gilles, S.

Clinical benefits of a randomized allergy app intervention in grass pollen sufferers: A controlled trial.

Allergy, DOI: 10.1111/all.16558 (2025)
Publ. Version/Full Text DOI PMC
Open Access Gold (Paid Option)
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BACKGROUND: Symptom monitoring can improve adherence to daily medication. However, controlled clinical trials on multi-modular allergy apps and their various functions have been difficult to implement. The objective of this study was to assess the clinical benefit of an allergy app with varying numbers of functions in reducing symptoms and improving quality of (QoL) life in grass pollen allergic individuals. The secondary objective was to develop a symptom forecast based on patient-derived and environmental data. METHODS: We performed a stratified, controlled intervention study (May-August 2023) with grass pollen allergic participants (N = 167) in Augsburg, Germany. Participants were divided into three groups, each receiving the same allergy app, but with increasing numbers of functions. PRIMARY ENDPOINT: rhinitis-related QoL; Secondary endpoints: symptom scores, relevant behavior, self-reported usefulness of the app, symptom forecast. RESULTS: Rhinitis-related QoL was increased after the intervention, with no statistical inter-group differences. However, participants with access to the full app version, including a pollen forecast, took more medication and reported lower symptoms and social activity impairment than participants with access to a reduced-function app. Using an XGBoost multiclass classification model, we achieved promising results for predicting nasal (accuracy: 0.79; F1-score: 0.78) and ocular (accuracy: 0.82; F1-score: 0.76) symptom levels and derived feature importance using SHAP as a guidance for future approaches. CONCLUSION: Our allergy app with its high-performance pollen forecast, symptom diary, and general allergy-related information provides a clinical benefit for allergy sufferers. Reliable symptom forecasts may be created given high-quality and high-resolution data.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Allergic Rhinitis ; Allergy App ; Clinical Study ; Pollen Forecast ; Symptom Forecast; Quality-of-life; Rhinoconjunctivitis; Validation; Symptoms; Rhinitis; Exposure; Season
ISSN (print) / ISBN 0105-4538
e-ISSN 1398-9995
Journal Allergy
Publisher Wiley
Publishing Place 111 River St, Hoboken 07030-5774, Nj Usa
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Environmental Medicine (IEM)
Grants Medical Faculty of the University of Augsburg
Bayerisches Landesamt fr Gesunheit und Lebensmittelsicherheit (LGL)