ArticleYonsei medical journal2025
Digital Phenotyping of Rare Endocrine Diseases Across International Data Networks and the Effect of Granularity of Original Vocabulary.
Article in Yonsei medical journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Epidemiology and clinical outcomes of clinically suspected multiple endocrine neoplasia type 1 in South Korea: a nationwide cohort study.Frontiers in endocrinology · 2025Article
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12 authors.
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Abstract
purposeRare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. MATERIALS AND
methodsDigital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital's electronic health record from South Korea; IQVIA's United Kingdom (UK) database for general practitioners; and IQVIA's United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea.
resultsThe positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%-62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34-2.07 (Korea), 0.13-0.30 (US); hypoparathyroidism, 0.40-1.20 (Korea), 0.59-1.01 (US), 0.00-1.78 (UK); and pheochromocytoma/paraganglioma, 0.95-1.67 (Korea), 0.35-0.77 (US), 0.00-0.49 (UK).
conclusionOur findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.
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