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