Abstract
Newborn screening (NBS) for cystic fibrosis (CF) offers the opportunity for early diagnosis and improved outcomes in patients with CF and has been universally available in the state of Massachusetts since 1999 using an immunoreactive trypsinogen (IRT)-DNA algorithm. Ideally, CF NBS is incorporated as part of an integrated NBS system that allows for comprehensive and coordinated education, laboratory screening, clinical follow-up, and evaluation so that evidence-based data can be used to maximize quality improvements and optimize the screening algorithm. The New England Newborn Screening Program (NENSP) retrospectively analyzed Massachusetts’s CF newborn screening data that yielded decisions to eliminate a screen-positive category, maintain the IRT cutoff value that prompts the second tier DNA testing, and communicate CF relative risk to primary care providers (PCPs) based on categorization of positive CF NBS results.
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This work was funded in part by The New England Newborn Screening Program of University of Massachusetts Medical School and HRSA grant U22MC03959 subcontract for Priority Focus 2.
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Communicated by: Bridget Wilcken
Competing interest: None declared.
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Hale, J.E., Parad, R.B., Dorkin, H.L. et al. Cystic fibrosis newborn screening: using experience to optimize the screening algorithm. J Inherit Metab Dis 33 (Suppl 2), 255–261 (2010). https://doi.org/10.1007/s10545-010-9117-3
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DOI: https://doi.org/10.1007/s10545-010-9117-3