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Treatment Algorithm for Infants Diagnosed with Spinal Muscular Atrophy through Newborn Screening

Overview of attention for article published in Journal of Neuromuscular Diseases, May 2018
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Treatment Algorithm for Infants Diagnosed with Spinal Muscular Atrophy through Newborn Screening
Published in
Journal of Neuromuscular Diseases, May 2018
DOI 10.3233/jnd-180304
Pubmed ID

Jacqueline Glascock, Jacinda Sampson, Amanda Haidet-Phillips, Anne Connolly, Basil Darras, John Day, Richard Finkel, R. Rodney Howell, Katherine Klinger, Nancy Kuntz, Thomas Prior, Perry B. Shieh, Thomas O. Crawford, Douglas Kerr, Jill Jarecki


Spinal muscular atrophy (SMA) is an autosomal recessive disease characterized by the degeneration of alpha motor neurons in the spinal cord, leading to muscular atrophy. SMA is caused by deletions or mutations in the survival motor neuron 1 gene (SMN1). In humans, a nearly identical copy gene, SMN2, is present. Because SMN2 has been shown to decrease disease severity in a dose-dependent manner, SMN2 copy number is predictive of disease severity. To develop a treatment algorithm for SMA-positive infants identified through newborn screening based upon SMN2 copy number. A working group comprised of 15 SMA experts participated in a modified Delphi process, moderated by a neutral third-party expert, to develop treatment guidelines. The overarching recommendation is that all infants with two or three copies of SMN2 should receive immediate treatment (nā€Š=ā€Š13). For those infants in which immediate treatment is not recommended, guidelines were developed that outline the timing and appropriate screens and tests to be used to determine the timing of treatment initiation. The identification SMA affected infants via newborn screening presents an unprecedented opportunity for achievement of maximal therapeutic benefit through the administration of treatment pre-symptomatically. The recommendations provided here are intended to help formulate treatment guidelines for infants who test positive during the newborn screening process.

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Geographical breakdown

Country Count As %
Unknown 139 100%

Demographic breakdown

Readers by professional status Count As %
Other 23 17%
Researcher 21 15%
Student > Master 18 13%
Student > Bachelor 12 9%
Student > Postgraduate 11 8%
Other 28 20%
Unknown 26 19%
Readers by discipline Count As %
Medicine and Dentistry 39 28%
Biochemistry, Genetics and Molecular Biology 18 13%
Neuroscience 13 9%
Nursing and Health Professions 12 9%
Pharmacology, Toxicology and Pharmaceutical Science 8 6%
Other 18 13%
Unknown 31 22%