Caroline Holzmann,Johannes Karg,Matthias Reiger,Rajiv Kharbal,Paola Romano,Sabrina Scheiwein,Claudia Khalfi,Anna Muzalyova,Jens O Brunner,Gertrud Hammel,Athanasios Damialis,Claudia Traidl-Hoffmann,María P Plaza,Stefanie Gilles
{"title":"Clinical Benefits of a Randomized Allergy App Intervention in Grass Pollen Sufferers: A Controlled Trial.","authors":"Caroline Holzmann,Johannes Karg,Matthias Reiger,Rajiv Kharbal,Paola Romano,Sabrina Scheiwein,Claudia Khalfi,Anna Muzalyova,Jens O Brunner,Gertrud Hammel,Athanasios Damialis,Claudia Traidl-Hoffmann,María P Plaza,Stefanie Gilles","doi":"10.1111/all.16558","DOIUrl":null,"url":null,"abstract":"BACKGROUND\r\nSymptom 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.\r\n\r\nMETHODS\r\nWe 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.\r\n\r\nPRIMARY ENDPOINT\r\nrhinitis-related QoL; Secondary endpoints: symptom scores, relevant behavior, self-reported usefulness of the app, symptom forecast.\r\n\r\nRESULTS\r\nRhinitis-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.\r\n\r\nCONCLUSION\r\nOur 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.","PeriodicalId":122,"journal":{"name":"Allergy","volume":"28 1","pages":""},"PeriodicalIF":12.6000,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Allergy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/all.16558","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ALLERGY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Allergy is an international and multidisciplinary journal that aims to advance, impact, and communicate all aspects of the discipline of Allergy/Immunology. It publishes original articles, reviews, position papers, guidelines, editorials, news and commentaries, letters to the editors, and correspondences. The journal accepts articles based on their scientific merit and quality.
Allergy seeks to maintain contact between basic and clinical Allergy/Immunology and encourages contributions from contributors and readers from all countries. In addition to its publication, Allergy also provides abstracting and indexing information. Some of the databases that include Allergy abstracts are Abstracts on Hygiene & Communicable Disease, Academic Search Alumni Edition, AgBiotech News & Information, AGRICOLA Database, Biological Abstracts, PubMed Dietary Supplement Subset, and Global Health, among others.