A revision to the United States national ALS registry’s algorithm to improve Case-Ascertainment

Affiliates Paul Mehta [1], Jaime Raymond [1], Moon Han [1], Reshma Punjani [1], Theodore Larson [1], James D. Berry [2], Benjamin Rix Brooks [3], BjÖrn Oskarrson [4], Stephen Goutman [5], Kevin Horton [1]


[1] Agency for Toxic Substances and Disease Registry/Centers for Disease Control and Prevention, Atlanta, GA, USA
[2] Sean M Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, MA, USA
[3] Carolinas Medical Center, Atrium Health, University of North Carolina School of Medicine – Charlotte Campus, Charlotte, NC, USA
[4] Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
[5] Department of Neurology, University of Michigan, Ann Arbor, MI, USA

Journal Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration
Summary This paper describes the effort by the National ALS Registry and research partners to measure the impact of updating its case-finding algorithm and the reclassification of the Registry’s diagnostic status nomenclature. The researchers use a retrospective analysis of Registry data from 2011-2017 to determine the qualifiers that convert “possible ALS” individuals into “confirmed ALS” or “likely ALS” over time. The team found that the existing Registry algorithm likely result in under-ascertainment of ALS cases and updating the algorithm will help the Registry more accurately depict the true disease burden of ALS in the US.
Link to paper Read the paper here!