A revision to the United States national ALS registry's algorithm to improve Case-Ascertainment. Issue 3 (3rd April 2023) - Mehta, Paul; Raymond, Jaime; Han, Moon; Punjani, Reshma; Larson, Theodore; Berry, James D.; Brooks, Benjamin Rix; Oskarsson, Björn; Goutman, Stephen a.; Horton, Kevin
Abstract: Objective: To evaluate the impact of 1) updating the existing algorithm to improve case-finding sensitivity and 2) reclassifying the Registry's diagnostic status nomenclature into four new categories ("confirmed ALS, " "likely ALS, " "undetermined ALS, " or "not ALS") versus the current three ("definite ALS, " "possible ALS, " or "not ALS") to be more inclusive and descriptive of cases and individuals. Methods: A retrospective analysis of Registry data from 2011–2017 was conducted to follow "possible ALS" individuals over time to determine what qualifier caused them to convert, if at all and when, to Registry-eligible cases (i.e. "confirmed ALS" or "likely ALS"). Results: In 2011, 720 individuals were classified by the Registry algorithm as having "possible ALS". By 2017, 42% of these had converted to Registry-eligible ALS cases. Approximately 14% of those who were identified solely based on an ALS prescription drug never converted to Registry-eligible cases. This analysis indicates that "possible ALS" individuals with a single prescription for an ALS drug should be converted to Registry-eligible cases which would add between 300–500 cases per year on average. Conclusions: The Registry's existing algorithm likely results in the under-ascertainment of ALS cases. However, updating the algorithm with the inclusion of patients having been prescribed ALS-specific drugs, even with a single prescription, leads to improved epidemiologic estimates of ALS in the US. This and future algorithmic updates will help the Registry more accurately depict the true disease burden of ALS in the US.