Diagnosis of Paediatric Inborn Errors of Immunity in a MENA Cohort Referred for Recurrent Infections Using a...

Area of Science:

• Pediatric Immunology
• Clinical Genetics
• Diagnostic Algorithms

Background:

• Recurrent infections in children can indicate underlying inborn errors of immunity (IEI).
• Accurate and timely diagnosis of IEI is crucial for effective management and improved patient outcomes.
• Existing diagnostic pathways may lack efficiency in identifying children with IEI.

Purpose of the Study:

• To assess the diagnostic performance of a structured, multistep algorithm for identifying inborn errors of immunity (IEI) in children referred for recurrent infections.
• To evaluate the algorithm's effectiveness in clinical triage and resource allocation.

Main Methods:

• A single-center study included 705 children (0-18 years) with recurrent infections.
• Screening utilized the Jeffrey Modell Foundation (JMF) and/or the Pan-Middle East (MENA) criteria.
• 132 children meeting criteria underwent stepwise immunologic evaluation, including advanced testing.

Main Results:

• 18.7% (132/705) of referred children met screening criteria.
• Inborn errors of immunity (IEI) were diagnosed in 7.1% (50/705) of all referred children, with a 71% confirmation rate.
• Common diagnoses included antibody deficiencies (32%) and syndromic combined immunodeficiencies (28%); 74% had pathogenic variants.

Conclusions:

• The structured diagnostic algorithm, incorporating JMF and MENA criteria, enhances IEI diagnosis and prioritizes patient care.
• This model optimizes resource utilization, reduces unnecessary testing, and facilitates prompt diagnosis, especially in resource-limited settings.
• The approach is practical and cost-effective, particularly beneficial in regions with high consanguinity and limited access to advanced diagnostics.