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Predicting CDR status over 36 months with a recall-based digital cognitive biomarker.

Davide Bruno1, Ainara Jauregi-Zinkunegi1, Jason R Bock2

  • 1School of Psychology, Liverpool John Moores University, Liverpool, UK.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|September 11, 2024
PubMed
Summary

Digital cognitive biomarkers (DCBs) derived from word-list recall tests, specifically latent recall ability (M), significantly outperform traditional Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) metrics in predicting dementia progression. Process scoring enhances cognitive assessment accuracy.

Keywords:
Alzheimer's Disease Assessment Scale–Cognitive subscaleClinical Dementia Ratingcognitive assessmentdigital cognitive biomarkers

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Biomarker Discovery

Background:

  • Word-list recall tests are standard for cognitive assessment.
  • Process scoring may enhance the accuracy of these cognitive tests.
  • Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) is a common cognitive assessment tool.

Purpose of the Study:

  • To evaluate if process-based digital cognitive biomarkers (DCBs) derived from ADAS-Cog predict longitudinal Clinical Dementia Rating (CDR) progression.
  • To compare the predictive accuracy of DCBs against standard ADAS-Cog scores.

Main Methods:

  • Utilized Alzheimer's Disease Neuroimaging Initiative (ADNI) data from 330 participants.
  • Performed regression analyses predicting CDR at 36 months.
  • Controlled for demographics and genetic risk, using ADAS-Cog scores and DCBs as predictors.

Main Results:

  • Latent recall ability (M), a DCB, was the strongest predictor of CDR at 36 months (AUC = 0.84).
  • M significantly outperformed traditional ADAS-Cog scores in predicting dementia decline.
  • The top DCB model demonstrated substantially higher predictive power (odds ≈ 90x) than the top ADAS-Cog model.

Conclusions:

  • Process scoring and latent modeling offer superior predictive accuracy compared to traditional scoring for cognitive tests.
  • The DCB 'M' shows potential for identifying individuals unlikely to experience cognitive decline.
  • Further research is warranted to explore the applicability of these DCBs across different tests and populations.