Clinical Validation of a Primary Antibody Deficiency Screening Algorithm for Primary Care

• Published in: Journal of clinical immunology Vol. 43; no. 8; pp. 2022 - 2032
• Main Authors: Messelink, Marianne A., Welsing, Paco M. J., Devercelli, Giovanna, Marsden, Jan Willem N., Leavis, Helen L.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.11.2023; Springer Nature B.V
• Subjects: Algorithms; antibodies; Biomedical and Life Sciences; Biomedicine; blood serum; confidence interval; cost effectiveness; data collection; Delayed Diagnosis; Electronic health records; Electronic medical records; health services; Humans; Immunoglobulins; Immunology; Infectious Diseases; Internal Medicine; Medical Microbiology; Morbidity; mortality; Netherlands; Original Article; Patients; Primary care; Primary Health Care; Primary Immunodeficiency Diseases; risk; Risk groups; telemedicine; Netherlands; primary care database; diagnostic delay; validation study; screening algorithm; Primary antibody deficiencies
• ISSN: 0271-9142; 1573-2592; 1573-2592
• DOI: 10.1007/s10875-023-01575-8

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