A Comparative Effectiveness Study of Newborn Screening Methods for Four Lysosomal Storage Disorders

Autor: Karen A. Sanders, Dimitar K. Gavrilov, Devin Oglesbee, Kimiyo M. Raymond, Silvia Tortorelli, John J. Hopwood, Fred Lorey, Ramanath Majumdar, Charles A. Kroll, Amber M. McDonald, Jean M. Lacey, Coleman T. Turgeon, Justin N. Tucker, Hao Tang, Robert Currier, Grazia Isaya, Piero Rinaldo, Dietrich Matern
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: International Journal of Neonatal Screening, Vol 6, Iss 2, p 44 (2020)
Druh dokumentu: article
ISSN: 2409-515X
DOI: 10.3390/ijns6020044
Popis: Newborn screening for one or more lysosomal disorders has been implemented in several US states, Japan and Taiwan by multiplexed enzyme assays using either tandem mass spectrometry or digital microfluidics. Another multiplex assay making use of immunocapture technology has also been proposed. To investigate the potential variability in performance of these analytical approaches, we implemented three high-throughput screening assays for the simultaneous screening for four lysosomal disorders: Fabry disease, Gaucher disease, mucopolysaccharidosis type I, and Pompe disease. These assays were tested in a prospective comparative effectiveness study using nearly 100,000 residual newborn dried blood spot specimens. In addition, 2nd tier enzyme assays and confirmatory molecular genetic testing were employed. Post-analytical interpretive tools were created using the software Collaborative Laboratory Integrated Reports (CLIR) to determine its ability to improve the performance of each assay vs. the traditional result interpretation based on analyte-specific reference ranges and cutoffs. This study showed that all three platforms have high sensitivity, and the application of CLIR tools markedly improves the performance of each platform while reducing the need for 2nd tier testing by 66% to 95%. Moreover, the addition of disease-specific biochemical 2nd tier tests ensures the lowest false positive rates and the highest positive predictive values for any platform.
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