The Utility of Study Insight Analytics (SIA) Algorithms in Identifying Scoring Error Risks in the Clinical Dementia Rating scale (CDR)
Selam Negash, Barbara Echevarria, Raymond Blattner, Christopher Randolph · 2025
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Description
Selam Negash, Barbara Echevarria, Raymond Blattner, and Christopher Randolph test analytics algorithms that flag scoring error risks in the Clinical Dementia Rating scale. Their 2025 paper deals with a key endpoint in many Alzheimer's disease trials.
Trial failure rates are high in part because endpoint measures are imprecise. Study Insight Analytics uses algorithms to find inconsistencies that may signal poor scale administration or scoring errors. The rating scale is hard to score, above all in early and mild disease. The team analyzed more than forty thousand reviewed assessments from 34 multinational trials. They built and validated algorithms for this scale and measured how often flags occurred and how they tracked real errors.
Catalog record
| CREATOR | Selam Negash, Barbara Echevarria, Raymond Blattner, Christopher Randolph |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 3 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |