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Updated: Jan 21, 2026
06:49
A Quick Phenotypic Neurological Scoring System for Evaluating Disease Progression in the SOD1-G93A Mouse Model of ALS
Published on: October 6, 2015
20.9K
ALS/SURV: a modification of the CAFS statistic
Stephen A Goutman1,2, Morton B Brown3, Merit Cudkowicz4
1Department of Neurology, University of Michigan , Ann Arbor , MI , USA.
Summary
A new composite endpoint, ALS/SURV, combines functional status and survival for amyotrophic lateral sclerosis (ALS) trials. It improves participant ranking, especially for those withdrawing, offering a more robust measure than CAFS.
Area of Science:
- Neurology
- Clinical Trials
- Biostatistics
Background:
- Amyotrophic lateral sclerosis (ALS) clinical trials require robust endpoints to assess treatment efficacy.
- Existing composite endpoints like CAFS may not adequately account for participant withdrawal or loss to follow-up.
- Accurate assessment of functional status and survival is crucial for evaluating interventions in ALS.
Purpose of the Study:
- To introduce and validate a novel composite endpoint, ALS/SURV, for amyotrophic lateral sclerosis (ALS) trials.
- To compare the performance of ALS/SURV against the Combined Assessment of Function and Survival (CAFS) score, particularly regarding participant dropout.
- To establish ALS/SURV as a statistically sound and clinically meaningful measure for ALS research.
Main Methods:
- Developed ALS/SURV by modifying and extending the CAFS score to incorporate functional status (ALS Functional Rating Scale) and survival.
- Implemented a ranking system within ALS/SURV that appropriately handles participants who withdraw or are lost to follow-up.
- Applied ALS/SURV and CAFS to data from a ceftriaxone treatment trial for ALS to compare participant rankings.
Main Results:
- ALS/SURV provides a ranking system that orders participants based on survival and functional status, without disproportionately skewing results due to dropouts.
- Comparison with CAFS demonstrated that ALS/SURV does not alter the study completion rankings based on withdrawal data.
- ALS/SURV allows for summary statistics (median, interquartile range) and enables confidence interval computation for power estimation in future studies.
Conclusions:
- ALS/SURV is a superior composite endpoint for ALS trials, offering improved handling of participant withdrawal compared to CAFS.
- The statistical properties of ALS/SURV support its use for more accurate and reliable assessment of therapeutic interventions in ALS.
- ALS/SURV provides a clinically meaningful and statistically robust measure for advancing ALS research and drug development.
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