Patient Trajectories from Electronic Health Records Suggest Specialty Specific Warning Signs for Common Variable Immunodeficiency
- 1University of California, Los Angeles
Abstract
BackgroundCommon variable immunodeficiency is frequently underrecognized due to its heterogeneous clinical presentation, resulting in diagnostic delays that increase disease-related complications, with each year of delay increasing mortality risk by 4% for the most common inborn error of immunity.
ObjectiveIn individuals with established common variable immunodeficiency, we sought to recognize patterns in patient diagnostic trajectories to identify opportunities for interventions to reduce time to diagnosis.
MethodsWe analyzed retrospective electronic health records data from 139 individuals with physician-confirmed common variable immunodeficiency across five academic health systems representing >10million patients. We evaluated diagnosing specialties and international classification of disease code trajectories in the two years prior to and at common variable immunodeficiency confirmation. Additionally, we construct specialty-specific prediction on a 1:50 case: control cohort using a gradient boosting algorithm.
ResultsThe leading diagnoses at common variable immunodeficiency determination were respiratory (35% of individuals), and individuals with respiratory symptoms were more likely to be diagnosed by Allergy / Immunology than by other specialties (odds ratio 2.9, standard error 0.35, p-value 1.9x10-3) and had a higher frequency of visits to pulmonary disease in the two years prior to diagnosis. Individuals with neoplasms were 50% more likely than other patients (OR 2.0, SE 0.29, p-value 0.02) to receive a diagnosis at each visit, reducing their diagnostic delay by up to a year. We find that a larger ratio of number of specialties visited to the total number of visits is significantly correlated with an increased time to diagnosis. A trajectory-informed specialty-specific prediction improved detection with an area under the precision-recall curve of fifty times the value expected under the null.
ConclusionsIndividuals referred to Allergy / Immunology have shorter time to diagnosis, and a specialty-specific prediction could improve detection of common variable immunodeficiency.
Clinical ImplicationsOverall, we find that phenotype-specialty interactions may inform targeted interventions to improve common variable immunodeficiency recognition across specialties, reducing diagnostic odyssey and disease-related complications.
Capsule SummarySpecialty-specific symptom patterns and patient trajectories preceding common variable immunodeficiency diagnosis reveal opportunities for earlier recognition through context-aware electronic health record-based prediction.
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BibTeX
@misc{mester2026patient,
title = {{Patient Trajectories from Electronic Health Records Suggest Specialty Specific Warning Signs for Common Variable Immunodeficiency}},
author = {R. Mester and A. T. Chin and V. Tozzo and A. V. Stephens and H. M. Hoffman and M. A. Riedl and M. J. Dorsey and S. Gupta and Y. Y. Demirdag and S. Sankararaman and L. Bastarache and B. Pasaniuc and M. J. Butte},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.01.26364525},
url = {https://www.medrxiv.org/content/10.64898/2026.10.01.26364525v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Patient Trajectories from Electronic Health Records Suggest Specialty Specific Warning Signs for Common Variable Immunodeficiency
AU - R. Mester
AU - A. T. Chin
AU - V. Tozzo
AU - A. V. Stephens
AU - H. M. Hoffman
AU - M. A. Riedl
AU - M. J. Dorsey
AU - S. Gupta
AU - Y. Y. Demirdag
AU - S. Sankararaman
AU - L. Bastarache
AU - B. Pasaniuc
AU - M. J. Butte
PY - 2026
DA - 2026/10/01
PB - medRxiv
DO - 10.64898/2026.10.01.26364525
UR - https://www.medrxiv.org/content/10.64898/2026.10.01.26364525v1
AB - BackgroundCommon variable immunodeficiency is frequently underrecognized due to its heterogeneous clinical presentation, resulting in diagnostic delays that increase disease-related complications, with each year of delay increasing mortality risk by 4% for the most common inborn error of immunity. ObjectiveIn individuals with established common variable immunodeficiency, we sought to recognize patterns in patient diagnostic trajectories to identify opportunities for interventions to reduce time to diagnosis. MethodsWe analyzed retrospective electronic health records data from 139 individuals with physician-confirmed common variable immunodeficiency across five academic health systems representing >10million patients. We evaluated diagnosing specialties and international classification of disease code trajectories in the two years prior to and at common variable immunodeficiency confirmation. Additionally, we construct specialty-specific prediction on a 1:50 case: control cohort using a gradient boosting algorithm. ResultsThe leading diagnoses at common variable immunodeficiency determination were respiratory (35% of individuals), and individuals with respiratory symptoms were more likely to be diagnosed by Allergy / Immunology than by other specialties (odds ratio 2.9, standard error 0.35, p-value 1.9x10-3) and had a higher frequency of visits to pulmonary disease in the two years prior to diagnosis. Individuals with neoplasms were 50% more likely than other patients (OR 2.0, SE 0.29, p-value 0.02) to receive a diagnosis at each visit, reducing their diagnostic delay by up to a year. We find that a larger ratio of number of specialties visited to the total number of visits is significantly correlated with an increased time to diagnosis. A trajectory-informed specialty-specific prediction improved detection with an area under the precision-recall curve of fifty times the value expected under the null. ConclusionsIndividuals referred to Allergy / Immunology have shorter time to diagnosis, and a specialty-specific prediction could improve detection of common variable immunodeficiency. Clinical ImplicationsOverall, we find that phenotype-specialty interactions may inform targeted interventions to improve common variable immunodeficiency recognition across specialties, reducing diagnostic odyssey and disease-related complications. Capsule SummarySpecialty-specific symptom patterns and patient trajectories preceding common variable immunodeficiency diagnosis reveal opportunities for earlier recognition through context-aware electronic health record-based prediction.
ER -