Methodology for the Development of the Allergic Rhinitis and Its Impact on Asthma (ARIA)-EAACI 2024–2025 Guidelines: From Evidence-to-Decision Frameworks to Digitalised Shared Decision-Making Algorithms - Bousquet, Jean; Sousa‐Pinto, Bernardo; Vieira, Rafael José; Schünemann, Holger J.; Zuberbier, Torsten; Bognanni, Antonio; Togias, Alkis; Samolinski, Boleslaw; Valiulis, Arunas; Williams, Sian; Bedbrook, Anna; Czarlewski, Wienczyslawa; et al. (Wiley, 2026)
The Allergic Rhinitis and its Impact on Asthma (ARIA) guidelines produced their first edition in 1999, with subsequent revisions in 2008, 2010, 2016 and 2019. A new iteration of ARIA—ARIA 2024–2025—in collaboration with EAACI is currently being developed, focusing on the management of allergic rhinitis. ARIA 2024–2025 follows the GRADE framework and is endorsed by the European Academy of Allergy and Clinical Immunology (EAACI). A set of approaches has been used to develop guideline questions, including surveying key opinion leaders and using artificial intelligence (AI)-based tools to analyse web searches on allergic rhinitis and to generate questions. Each prioritised guideline question is assessed through an Evidence-to-Decision (EtD) framework. EtDs support the systematic and transparent formulation of recommendations, comprising 12 criteria for which the best available evidence should be sought. In the context of ARIA-EAACI 2024–2025, such evidence is derived not only from randomised controlled trials but also—among others—from patient-generated data sources that better reflect the affected individuals' perspectives. Moreover, ARIA-EAACI 2024–2025 incorporates evidence on planetary health. Developed guideline recommendations will support the creation of digitalised decision algorithms and care pathways. This paper describes the methodology used to develop the person-centred, digitally enabled and AI-assisted ARIA-EAACI 2024–2025. Among others, it describes (i) the development and prioritisation of guideline questions, (ii) sources of evidence for EtDs and (iii) the development of digitalised decision algorithms and care pathways.