ArticleThe journal of allergy and clinical immunology. Global2026
Identifying unmet needs in food protein-induced enterocolitis syndrome using search query analysis and a large language model.
Article in The journal of allergy and clinical immunology. Global, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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11 authors.
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Abstract
Background: Food protein-induced enterocolitis syndrome (FPIES) is a non-IgE-mediated food allergy with many unanswered clinical and research questions. Existing educational resources, patient-facing education materials, and guidelines may not fully reflect families' information needs. Digital data and artificial intelligence (AI) offer new ways to identify public concerns in rare diseases. Objective: We developed a framework utilizing online search data and AI-assisted analysis to generate data-informed questions for future patient advice guidance and educational resource development in FPIES, and evaluate these questions with parents/guardians. Methods: We collected Google Trends data from January 2023 to December 2024 to identify search queries related to FPIES in the United States. Using ChatGPT, query terms and frequencies were analyzed to generate 10 representative questions reflecting public interest. Parents/guardians of children with FPIES enrolled onto the Boston Children's Hospital FPIES Registry were surveyed to evaluate these questions. Results: Forty-four parents/guardians completed the survey (93.2% mothers; median [interquartile range] child age was 3.0 [2.0, 5.0] years). Nearly half (43.2%) reported more than one FPIES trigger food. Nine of 10 AI-generated questions were rated "important" or "very important" by >90% of participants, confirming their relevance. Questions most frequently reported as difficult to find answers for were managing reactions, outgrowing FPIES, and distinguishing FPIES from other allergies. Similar topics were selected as research priorities. Conclusion: A framework built from Google Trends data and AI-supported analysis can generate questions that align closely with parent/guardian priorities, offering a practical approach to informing patient advice guidance and educational resource development, with the ultimate goal of supporting patient-centered guideline development in FPIES.
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