Abstract
Objective: Amyotrophic lateral sclerosis (ALS) is a multi-system disorder characterized primarily by motor neuron degeneration, but may be accompanied by cognitive dysfunction. Statistically appropriate criteria for establishing cognitive impairment (CI) in ALS are lacking. We evaluate quantile regression (QR), that accounts for age and education, relative to a traditional two standard deviation (SD) cutoff for defining CI. Methods: QR of cross-sectional data from a multi-center North American Control (NAC) cohort of 269 healthy adults was used to model the 5th percentile of cognitive scores on the Edinburgh Cognitive and Behavioral ALS Screen (ECAS). The QR approach was compared to traditional two SD cutoff approach using the same NAC cohort (2SD-NAC) and to existing UK-based normative data derived using the 2SD approach (2SD-UK) to assess the impact of cohort selection and statistical model in identifying CI in 182 ALS patients. Results: QR-NAC models revealed that age and education impact cognitive performance on the ECAS. Based on QR-NAC normative cutoffs, the frequency of CI in the 182 PENN ALS patients was 15.9% for ALS specific, 12.6% for ALS nonspecific, and 15.4% for ECAS total. This frequency of CI is substantially more conservative in comparison to the 2SD-UK (20.3%–34.6%) and modestly more conservative to the 2SD-NAC (14.3%–16.5%) approaches for estimating CI. Conclusions: The choice of normative cohort has a substantial impact and choice of statistical method a modest impact on defining CI in ALS. This report establishes normative ECAS thresholds to identify whether ALS patients in the North American population have CI.
Acknowledgements
The authors extend thanks to research coordinators at the University of Pennsylvania including Laura Baehr, Laura Hennessy, and Hayley Donaldson for their efforts with participant recruitment and evaluation. CALSNIC additionally thanks the research team for participant recruitment and evaluations. In addition, CRiALS extends thanks to the research team at the University of Miami for participant recruitment and evaluation (Anne-Laure Grignon, Danielle Dauphin, Danielle Sheldon, Sumaira Hussain, Anne Cooley, Jessica Medina, Ashley Manso).
Disclosure statement
Dr. McMillan receives research funding outside the submitted work from Biogen, Inc. and provides consulting services for personal fees from Invicro and Axon Advisors on behalf of Translational Bioinformatics, LLC. He also receives an honorarium as Associate Editor of NeuroImage: Clinical.
Dr. Johnston receives research funding from Annexon, Alexion, ALS-Pharma, Biogen, Cytokinetics, Mallinckrodt, Mitsubishi-Tanabe Canada, Orion, and serves as a paid consultant to Biogen and Mitsubishi-Tanabe Canada.
Dr. Genge provides consulting services for the following companies: AB Sciences, Akcea, Alexion, AL-S Pharma, Anavex, Avexis, Bayshore, Biogen, Clene, CSL Behring, Cytokinetics, QurAlis, Mitsubishi Tenabe Pharma America, Novartis, Orion, Revalesio, Roche, Sanofi Genzyme, and Wave life sciences. She is also CRU Medical Director, PI or sub-PI on trials sponsored by the following companies: AB Sciences, AL-S Pharma, Acceleron, Amicus, Alnylam, Bioblast, Biogen, BMS, Boston Biomedical, Cytokinetics, Sanofi Genzyme, Grifols, Ionis, Lily, Mallinckrodt, Medimmune, Novartis, Orion, Orphazyme, Pfizer, Ra Pharmaceuticals, Roche, Teva, and UCB.
Dr. Benatar reports personal fees from Roche and Biogen.
Drs. Wuu, Rascovsky, Cosentino, Grossman, Elman, Quinn, Rosario, Stark, Granit, Briemberg, Chenji, Dionne, Korngut, Shoesmith, Zinman report no conflicts of interest.