Establishing diagnostic criteria for severe combined immunodeficiency disease (SCID), leaky SCID, and Omenn syndrome: The Primary Immune Deficiency Treatment Consortium experience

Abstract

Background The approach to the diagnosis of Severe Combined Immunodeficiency Disease (SCID) and related disorders varies among institutions and countries. Objectives The Primary Immune Deficiency Treatment Consortium (PIDTC) attempted to develop a uniform set of criteria for diagnosing SCID and related disorders, and has evaluated the results as part of a retrospective study of SCID in North America. Methods Clinical records from 2000 through 2009 at 27 centers in North America were collected on 332 children treated with hematopoietic cell transplant (HCT), enzyme replacement therapy (ERT) or gene therapy (GT) for SCID and related disorders. Eligibility for inclusion in the study and classification into disease groups were established by set criteria and applied by an expert review group. Result Two hundred eighty-five (86%) of the patients were determined to be eligible and 47 (14%) were not eligible. Of the 285 eligible patients, 84% were classified as typical SCID; 13% were classified as leaky SCID, Omenn syndrome, or reticular dysgenesis; and 3% had a history of enzyme replacement or gene therapy. Detection of a genotype predicting a SCID phenotype was accepted for eligibility. Reasons for non-eligibility were failure to demonstrate either impaired lymphocyte proliferation or maternal T cell engraftment. Overall (n = 332) rates of testing were: proliferation to PHA 77%, maternal engraftment 35%, and genotype 79% (mutation identified in 62%). Conclusion Lack of complete laboratory evaluation of patients prior to HCT presents a significant barrier to definitive diagnosis of SCID and related disorders and prevented inclusion of individuals in our observational HCT study. This lesson is critical for patient care as well as the design of future, prospective treatment studies for such children, since a well-defined and consistent study population is important for precision in outcomes analysis.