Din Abdul Jabbar, M. A., Guo, L., Guo, Y., Simmons, Z., Pioro, E. P., Ramasamy, S., Yeo, C. J. J. (2023). Describing and characterising variability in ALS disease progression. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 1–12. https://doi.org/10.1080/21678421.2023.2260838
Abstract:
Background,Objectives: Decrease in the revised ALS Functional Rating Scale (ALSFRS-R) score is currently the most widelyused measure of disease progression. However, it does not sufficiently encompass the heterogeneity of ALS. We describe ameasure of variability in ALSFRS-R scores and demonstrate its utility in disease characterization.Methods:Weused5030ALS clinical trial patients from the Pooled Resource Open-Access ALS Clinical Trials database to calculate variability in dis-ease progression employing a novel measure and correlated variability with disease span. We characterized the more and lessvariable populations and designed a machine learning model that used clinical, laboratory and demographic data to predictclass of variability. The model was validated with a holdout clinical trial dataset of 84 ALS patients (NCT00818389).Results: Greater variability in disease progression was indicative of longer disease span on the patient-level. The machinelearning model was able to predict class of variability with accuracy of 60.1–72.7% across different time periods and yieldeda set of predictors based on clinical, laboratory and demographic data. A reduced set of 16 predictors and the holdout data-set yielded similar accuracy.Discussion: This measure of variability is a significant determinant of disease span for fast-progressing patients. The predictors identified may shed light on pathophysiology of variability, with greater variability infast-progressing patients possibly indicative of greater compensatory reinnervation and longer disease span. Increasingvariability alongside decreasing rate of disease progression could be a future aim of trials for faster-progressing patients.
License type:
Publisher Copyright
Funding Info:
There was no specific funding for the research done
Description:
This is an Accepted Manuscript of an article published by Taylor & Francis in Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration on 05 October 2023, available online: http://www.tandfonline.com/doi.org/10.1080/21678421.2023.2260838