1. Evaluation of the Genetic Screening Processor for the Performance of Newborn Screening Tests
- Author
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André Canto de Souza, Simone Martins de Castro, Letícia Filippon, and Raquel Weber
- Subjects
validation ,lcsh:R5-920 ,Pediatrics ,medicine.medical_specialty ,Newborn screening ,Filter paper ,newborn screening ,business.industry ,Endocrinology, Diabetes and Metabolism ,IRT ,NTSH ,17OHP ,Pediatrics, Perinatology and Child Health ,Medicine ,lcsh:Medicine (General) ,business ,Dried blood ,Genetics (clinical) ,GSP - Abstract
The collection of dried blood spots (DBSs) on filter paper has been a powerful tool in newborn screening (NBS) programs and in other fields. However, filter paper has been associated with some level of imprecision due to the filter paper matrix effect. In order to minimize measurement variations, these interferences should be evaluated by NBS assays. The aim of this study is to evaluate the performance of genetic screening processor (GSP) equipment in comparison with a widely used AutoDELFIA and to discuss the limitations and advantages of this new technology in NBS. We evaluated the performance of 3 NBS assays in DBS using GSP in comparison with AutoDELFIA. To determine the inaccuracy and the intra-assay precision, a comparative study and a replication experiment were performed. In the comparative study, human thyroid-stimulating hormone (hTSH) assay showed the highest correlation coefficient, followed by 17α-OH-progesterone and immunoreactive trypsinogen (IRT) assays. The results of the present study suggest that the GSP equipment and kits are suitable for implementation and have acceptable performance for NBS routine. Genetic screening processor assay tends to underestimate hTSH and IRT concentrations in the clinically relevant range when compared to AutoDELFIA assays. More studies are necessary to reevaluate cutoff values. Furthermore, the equipment has advantages when compared with AutoDELFIA, such as methodology with more specificity, reduction in the processing time, and randomized routine. This helps promoting faster dynamic technical processes and faster report generation.
- Published
- 2016
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