AI Article Synopsis
- Composite scores, like the AD Composite Score (ADCOMS), are used in Alzheimer's trials to monitor disease progression, prompting the development of a new scoring system.
- The new composite score, ADSS, was created by refining existing statistical models and incorporating cognitive sub-scales to enhance detection of disease changes.
- ADSS shows better sensitivity in identifying disease progression, potentially reducing sample sizes needed for trials and improving drug development success rates.
Article Abstract
Background: Composite scores have been increasingly used in trials for Alzheimer's disease (AD) to detect disease progression, such as the AD Composite Score (ADCOMS) in the lecanemab trial.
Objective: To develop a new composite score to improve the prediction of outcome change.
Methods: We proposed to develop a new composite score based on the statistical model in the ADCOMS, by removing duplicated sub-scales and adding the model selection in the partial least squares (PLS) regression.
Results: The new composite core with variable election (ADSS) includes 7 cognitive sub-scales. ADSS can increase the sensitivity to detect disease progression as compared to the existing total scores, which leads to smaller sample sizes using the ADSS in trial designs.
Conclusions: ADSS can be utilized in AD trials to improve the success rate of drug development with a high sensitivity to detect disease progression in early stages.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10894615 | PMC |
| http://dx.doi.org/10.3233/ADR-230043 | DOI Listing |
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