Article ; Online: Validating inborn error of immunity prevalence and risk with nationally representative electronic health record data.
The Journal of allergy and clinical immunology
2024
Abstract: Background: The 10 Warning Signs of Primary Immunodeficiency were created 30 years ago to advance recognition of inborn errors of immunity (IEI). However, no population-level assessment of their utility applied to electronic health record (EHR) data has ...
| Abstract | Background: The 10 Warning Signs of Primary Immunodeficiency were created 30 years ago to advance recognition of inborn errors of immunity (IEI). However, no population-level assessment of their utility applied to electronic health record (EHR) data has been conducted. Objective: We sought to quantify the value of having ≥2 warning signs (WS) toward diagnosing IEI using a highly representative real-world US cohort. A secondary goal was estimating the US prevalence of IEI. Methods: In this cohort study, we accessed normalized and de-identified EHR data on 152 million US patients. An IEI cohort (n = 41,080), in which patients were defined by having at least 1 verifiable IEI diagnosis placed ≥2 times in their record, was compared with a matched set of controls (n = 250,262). WS were encoded along with relevant diagnoses, relative weights were calculated, and the proportion of IEI cases versus controls with ≥2 WS was compared. Results: The proportion of IEI cases with ≥2 WS significantly differed from controls (0.33 vs 0.031; P < .0005, χ Conclusions: This nationally representative US-based cohort study demonstrates that presence of WS and associated clinical diagnoses can facilitate identification of patients with IEI from EHR data. In addition, we estimate that 6 in 10,000, or approximately 150,000 to 200,000 individuals are affected by IEI across the United States. |
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| Language | English |
| Publishing date | 2024-01-24 |
| Publishing country | United States |
| Document type | Journal Article |
| ZDB-ID | 121011-7 |
| ISSN | 1097-6825 ; 1085-8725 ; 0091-6749 |
| ISSN (online) | 1097-6825 ; 1085-8725 |
| ISSN | 0091-6749 |
| DOI | 10.1016/j.jaci.2024.01.011 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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