BACKGROUND: The advent of tandem mass spectrometry has made it possible to test newborns for multiple conditions efficiently. It is not known how state newborn screening programs have changed screening practices in response to this technology and how it affects the number of false-positive test results. METHODS: We obtained data from the National Newborn Screening and Genetics Resource Center regarding the screening practices for each of the 50 states, to determine the number of mandated disorders added to state newborn screening panels between 1995 and 2005. Combining these data with reported specificities from the literature and the number of births in each state, we estimated the number of infants who would have received false-positive results through screening with tandem mass spectrometry in 2005. RESULTS: The average state mandated screening for 5 disorders in 1995 (range: 0-8 disorders). Wyoming was the only state that decreased its panel size over the next decade. Kansas and Texas were the only states that did not add disorders to their panels between 1995 and 2005; the average state added 19. Iowa, Minnesota, Mississippi, South Dakota, and Tennessee each added > or = 40 disorders. Assuming that an individual test for a disorder had a specificity of 99.995%, we estimated that approximately 2575 infants would have received false-positive results through screening with tandem mass spectrometry in 2005. If specificity was assumed to be 99.9%, then the number increased to > 51000. CONCLUSIONS: State newborn screening programs have expanded dramatically in the past decade. Because the benefit of such testing may be unclear in some cases and because the number of infants who may receive false-positive results and may be labeled falsely as having disease is potentially sizeable, a more cautious approach is needed.
BACKGROUND: The advent of tandem mass spectrometry has made it possible to test newborns for multiple conditions efficiently. It is not known how state newborn screening programs have changed screening practices in response to this technology and how it affects the number of false-positive test results. METHODS: We obtained data from the National Newborn Screening and Genetics Resource Center regarding the screening practices for each of the 50 states, to determine the number of mandated disorders added to state newborn screening panels between 1995 and 2005. Combining these data with reported specificities from the literature and the number of births in each state, we estimated the number of infants who would have received false-positive results through screening with tandem mass spectrometry in 2005. RESULTS: The average state mandated screening for 5 disorders in 1995 (range: 0-8 disorders). Wyoming was the only state that decreased its panel size over the next decade. Kansas and Texas were the only states that did not add disorders to their panels between 1995 and 2005; the average state added 19. Iowa, Minnesota, Mississippi, South Dakota, and Tennessee each added > or = 40 disorders. Assuming that an individual test for a disorder had a specificity of 99.995%, we estimated that approximately 2575 infants would have received false-positive results through screening with tandem mass spectrometry in 2005. If specificity was assumed to be 99.9%, then the number increased to > 51000. CONCLUSIONS: State newborn screening programs have expanded dramatically in the past decade. Because the benefit of such testing may be unclear in some cases and because the number of infants who may receive false-positive results and may be labeled falsely as having disease is potentially sizeable, a more cautious approach is needed.
Authors: Jonathan S Berg; Pankaj B Agrawal; Donald B Bailey; Alan H Beggs; Steven E Brenner; Amy M Brower; Julie A Cakici; Ozge Ceyhan-Birsoy; Kee Chan; Flavia Chen; Robert J Currier; Dmitry Dukhovny; Robert C Green; Julie Harris-Wai; Ingrid A Holm; Brenda Iglesias; Galen Joseph; Stephen F Kingsmore; Barbara A Koenig; Pui-Yan Kwok; John Lantos; Steven J Leeder; Megan A Lewis; Amy L McGuire; Laura V Milko; Sean D Mooney; Richard B Parad; Stacey Pereira; Joshua Petrikin; Bradford C Powell; Cynthia M Powell; Jennifer M Puck; Heidi L Rehm; Neil Risch; Myra Roche; Joseph T Shieh; Narayanan Veeraraghavan; Michael S Watson; Laurel Willig; Timothy W Yu; Tiina Urv; Anastasia L Wise Journal: Pediatrics Date: 2017-01-17 Impact factor: 7.124
Authors: Karen M Meagher; Michelle L McGowan; Richard A Settersten; Jennifer R Fishman; Eric T Juengst Journal: Annu Rev Genomics Hum Genet Date: 2017-04-24 Impact factor: 8.929
Authors: James D Weisfeld-Adams; Mark A Morrissey; Brian M Kirmse; Bobbie R Salveson; Melissa P Wasserstein; Peter J McGuire; Sherlykutty Sunny; Jessica L Cohen-Pfeffer; Chunli Yu; Michele Caggana; George A Diaz Journal: Mol Genet Metab Date: 2009-09-27 Impact factor: 4.797