Describing and characterising variability in ALS disease progression

Decrease in the revised ALS Functional Rating Scale (ALSFRS-R) score is currently the most widely used measure of disease progression. However, it does not sufficiently encompass the heterogeneity of ALS. We describe a measure of variability in ALSFRS-R scores and demonstrate its utility in disease...

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Bibliographic Details
Published in:Amyotrophic lateral sclerosis and frontotemporal degeneration 2024-02, Vol.25 (1-2), p.34-45
Main Authors: Din Abdul Jabbar, Muzammil Arif, Guo, Ling, Guo, Yang, Simmons, Zachary, Pioro, Erik P, Ramasamy, Savitha, Yeo, Crystal Jing Jing
Format: Article
Language:English
Subjects:
Amyotrophic Lateral Sclerosis - diagnosis
Disease Progression
Humans
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Summary:Decrease in the revised ALS Functional Rating Scale (ALSFRS-R) score is currently the most widely used measure of disease progression. However, it does not sufficiently encompass the heterogeneity of ALS. We describe a measure of variability in ALSFRS-R scores and demonstrate its utility in disease characterization. We used 5030 ALS clinical trial patients from the Pooled Resource Open-Access ALS Clinical Trials database to calculate variability in disease progression employing a novel measure and correlated variability with disease span. We characterized the more and less variable populations and designed a machine learning model that used clinical, laboratory and demographic data to predict class of variability. The model was validated with a holdout clinical trial dataset of 84 ALS patients (NCT00818389). Greater variability in disease progression was indicative of longer disease span on the patient-level. The machine learning model was able to predict class of variability with accuracy of 60.1-72.7% across different time periods and yielded a set of predictors based on clinical, laboratory and demographic data. A reduced set of 16 predictors and the holdout dataset yielded similar accuracy. 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 in fast-progressing patients possibly indicative of greater compensatory reinnervation and longer disease span. Increasing variability alongside decreasing rate of disease progression could be a future aim of trials for faster-progressing patients.
ISSN:2167-8421
2167-9223
DOI:10.1080/21678421.2023.2260838