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Clinical Validation of a Primary Antibody Deficiency Screening Algorithm for Primary Care
Marianne A Messelink1, Paco M J Welsing2, Giovanna Devercelli3
1Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, Netherlands. m.a.messelink@umcutrecht.nl.
Insights
A new screening algorithm effectively identifies patients with primary antibody deficiencies (PADs) in primary care, reducing diagnostic delays. This validated tool significantly increases PAD detection rates compared to the general population.
Area of Science:
- Immunology
- Primary Care Medicine
- Health Informatics
Background:
- Diagnostic delay in primary antibody deficiencies (PADs) leads to severe health consequences and increased costs.
- Early detection of PADs is crucial for improving patient outcomes.
- A screening algorithm was previously developed to aid early PAD detection in primary care settings.
Purpose of the Study:
- To clinically validate and optimize a screening algorithm for early detection of primary antibody deficiencies (PADs).
- To apply the algorithm to a large primary care electronic health record (EHR) database in the Netherlands.
Main Methods:
- The screening algorithm was applied to 61,172 EHRs.
- High-scoring EHRs underwent exclusion screening, followed by serum immunoglobulin analysis for eligible patients.
- The algorithm was refitted using high-risk patient data to enhance efficiency.
Main Results:
- The study identified 10 new PAD patients, significantly increasing the detection rate (approx. 1:10) compared to the general population (1:1700-1:25,000).
- Refitting the algorithm improved its performance (AUC-ROC 0.80).
- A proposed two-step screening process involves initial broad screening followed by optimized selection for laboratory analysis.
Conclusions:
- The validated screening algorithm successfully reduces diagnostic delay for primary antibody deficiencies in primary care.
- The optimized algorithm and proposed two-step process enhance screening efficiency.
- Further validation in diverse populations and cost-effectiveness analyses are recommended.
Purpose:
The diagnostic delay of primary antibody deficiencies (PADs) is associated with increased morbidity, mortality, and healthcare costs. Therefore, a screening algorithm was previously developed for the early detection of patients at risk of PAD in primary care. We aimed to clinically validate and optimize the PAD screening algorithm by applying it to a primary care database in the Netherlands.
Methods:
The algorithm was applied to a data set of 61,172 electronic health records (EHRs). Four hundred high-scoring EHRs were screened for exclusion criteria, and remaining patients were invited for serum immunoglobulin analysis and referred if clinically necessary.
Results:
Of the 104 patients eligible for inclusion, 16 were referred by their general practitioner for suspected PAD, of whom 10 had a PAD diagnosis. In patients selected by the screening algorithm and included for laboratory analysis, prevalence of PAD was ~ 1:10 versus 1:1700-1:25,000 in the general population. To optimize efficiency of the screening process, we refitted the algorithm with the subset of high-risk patients, which improved the area under the curve-receiver operating characteristics curve value to 0.80 (95% confidence interval 0.63-0.97). We propose a two-step screening process, first applying the original algorithm to distinguish high-risk from low-risk patients, then applying the optimized algorithm to select high-risk patients for serum immunoglobulin analysis.
Conclusion:
Using the screening algorithm, we were able to identify 10 new PAD patients from a primary care population, thus reducing diagnostic delay. Future studies should address further validation in other populations and full cost-effectiveness analyses.
Registration:
Clinicaltrials.gov record number NCT05310604, first submitted 25 March 2022.
