Holzmann Caroline, Karg Johannes, Reiger Matthias, Kharbal Rajiv, Romano Paola, Scheiwein Sabrina, Khalfi Claudia, Muzalyova Anna, Brunner Jens O, Hammel Gertrud, Damialis Athanasios, Traidl-Hoffmann Claudia, Plaza María P, Gilles Stefanie
Institute of Environmental Medicine and Integrative Health, Faculty of Medicine, University Hospital Augsburg, Augsburg, Germany.
Institute of Environmental Medicine, Helmholtz Munich-German Research Center for Environmental Health, Augsburg, Germany.
Allergy. 2025 Jul;80(7):1945-1955. doi: 10.1111/all.16558. Epub 2025 Apr 17.
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.
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.
rhinitis-related QoL; Secondary endpoints: symptom scores, relevant behavior, self-reported usefulness of the app, symptom forecast.
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.
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.
症状监测可提高每日用药的依从性。然而，针对多模块过敏应用程序及其各种功能的对照临床试验一直难以开展。本研究的目的是评估具有不同功能数量的过敏应用程序在减轻草花粉过敏个体的症状和改善生活质量（QoL）方面的临床益处。次要目的是根据患者来源的数据和环境数据制定症状预测。
我们于2023年5月至8月在德国奥格斯堡对草花粉过敏参与者（N = 167）进行了一项分层对照干预研究。参与者被分为三组，每组都使用相同的过敏应用程序，但功能数量逐渐增加。
与鼻炎相关的生活质量；次要终点：症状评分、相关行为、应用程序的自我报告有用性、症状预测。
干预后与鼻炎相关的生活质量有所提高，组间无统计学差异。然而，能够使用完整应用程序版本（包括花粉预测）的参与者比使用功能减少的应用程序的参与者服用了更多药物，并且报告的症状和社交活动受损程度更低。使用XGBoost多类分类模型，我们在预测鼻部（准确率：0.79；F1分数：）和眼部（准确率：0.82；F1分数：0.76）症状水平方面取得了有希望的结果，并以SHAP为指导得出特征重要性，为未来方法提供参考。
我们的过敏应用程序及其高性能的花粉预测、症状日记和一般过敏相关信息为过敏患者提供了临床益处。鉴于高质量和高分辨率的数据，可以创建可靠的症状预测。 0.78
