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Published on: May 10, 2024
Development and validation of a registry-based definition of eosinophilic esophagitis in Denmark
Evan S Dellon1, Rune Erichsen, Lars Pedersen
1Center for Esophageal Diseases and Swallowing, and Center for Gastrointestinal Biology and Disease, Division of Gastroenterology and Hepatology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC 27599-7080, USA. edellon@med.unc.edu
Aim:
To develop and validate a case definition of eosinophilic esophagitis (EoE) in the linked Danish health registries.
Methods:
For case definition development, we queried the Danish medical registries from 2006-2007 to identify candidate cases of EoE in Northern Denmark. All International Classification of Diseases-10 (ICD-10) and prescription codes were obtained, and archived pathology slides were obtained and re-reviewed to determine case status. We used an iterative process to select inclusion/exclusion codes, refine the case definition, and optimize sensitivity and specificity. We then re-queried the registries from 2008-2009 to yield a validation set. The case definition algorithm was applied, and sensitivity and specificity were calculated.
Results:
Of the 51 and 49 candidate cases identified in both the development and validation sets, 21 and 24 had EoE, respectively. Characteristics of EoE cases in the development set [mean age 35 years; 76% male; 86% dysphagia; 103 eosinophils per high-power field (eos/hpf)] were similar to those in the validation set (mean age 42 years; 83% male; 67% dysphagia; 77 eos/hpf). Re-review of archived slides confirmed that the pathology coding for esophageal eosinophilia was correct in greater than 90% of cases. Two registry-based case algorithms based on pathology, ICD-10, and pharmacy codes were successfully generated in the development set, one that was sensitive (90%) and one that was specific (97%). When these algorithms were applied to the validation set, they remained sensitive (88%) and specific (96%).
Conclusion:
Two registry-based definitions, one highly sensitive and one highly specific, were developed and validated for the linked Danish national health databases, making future population-based studies feasible.
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