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 |
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! |