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Primary care detection of Alzheimer's disease using a self-administered digital cognitive test and blood biomarkers

Tideman, Pontus LU ; Karlsson, Linda LU orcid ; Strandberg, Olof LU ; Calling, Susanna LU ; Smith, Ruben LU ; Midlöv, Patrik LU orcid ; Verghese, Philip B ; Braunstein, Joel B ; Mattsson-Carlgren, Niklas LU orcid and Stomrud, Erik LU orcid , et al. (2025) In Nature Medicine
Abstract

After the clinical implementation of amyloid-β-targeting therapies for people with cognitive impairment due to Alzheimer's disease (AD), there is an urgent need to efficiently identify this patient population in primary care. Therefore, we created a brief and self-administered digital cognitive test battery (BioCog). Based on its sub-scores, a logistic regression model was developed in a secondary care cohort (n = 223) and then evaluated in an independent primary care cohort comprising 19 primary care centers (n = 403). In primary care, BioCog had an accuracy of 85% when using a single cutoff to define cognitive impairment, which was significantly better than the assessment of primary care physicians (accuracy 73%). The accuracy... (More)

After the clinical implementation of amyloid-β-targeting therapies for people with cognitive impairment due to Alzheimer's disease (AD), there is an urgent need to efficiently identify this patient population in primary care. Therefore, we created a brief and self-administered digital cognitive test battery (BioCog). Based on its sub-scores, a logistic regression model was developed in a secondary care cohort (n = 223) and then evaluated in an independent primary care cohort comprising 19 primary care centers (n = 403). In primary care, BioCog had an accuracy of 85% when using a single cutoff to define cognitive impairment, which was significantly better than the assessment of primary care physicians (accuracy 73%). The accuracy increased to 90% when using a two-cutoff approach. BioCog had significantly higher accuracy than standard paper-and-pencil tests (that is, Mini-Mental State Examination, Montreal Cognitive Assessment, Mini-Cog) and another digital cognitive test. Furthermore, BioCog combined with a blood test could detect clinical, biomarker-verified AD with an accuracy of 90% (one cutoff), significantly better than standard-of-care (accuracy 70%) or when using the blood test alone (accuracy 80%). In conclusion, this proof-of-concept study shows that a brief, self-administered digital cognitive test battery can detect cognitive impairment and, when combined with a blood test, accurately identify clinical AD in primary care.

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organization
publishing date
type
Contribution to journal
publication status
epub
subject
in
Nature Medicine
publisher
Nature Publishing Group
external identifiers
  • scopus:105016223421
  • pmid:40954312
ISSN
1546-170X
DOI
10.1038/s41591-025-03965-4
language
English
LU publication?
yes
additional info
© 2025. The Author(s).
id
6f33cff3-40b8-4b89-b149-74f7e18ebc24
date added to LUP
2025-09-21 19:10:03
date last changed
2025-10-20 07:47:02
@article{6f33cff3-40b8-4b89-b149-74f7e18ebc24,
  abstract     = {{<p>After the clinical implementation of amyloid-β-targeting therapies for people with cognitive impairment due to Alzheimer's disease (AD), there is an urgent need to efficiently identify this patient population in primary care. Therefore, we created a brief and self-administered digital cognitive test battery (BioCog). Based on its sub-scores, a logistic regression model was developed in a secondary care cohort (n = 223) and then evaluated in an independent primary care cohort comprising 19 primary care centers (n = 403). In primary care, BioCog had an accuracy of 85% when using a single cutoff to define cognitive impairment, which was significantly better than the assessment of primary care physicians (accuracy 73%). The accuracy increased to 90% when using a two-cutoff approach. BioCog had significantly higher accuracy than standard paper-and-pencil tests (that is, Mini-Mental State Examination, Montreal Cognitive Assessment, Mini-Cog) and another digital cognitive test. Furthermore, BioCog combined with a blood test could detect clinical, biomarker-verified AD with an accuracy of 90% (one cutoff), significantly better than standard-of-care (accuracy 70%) or when using the blood test alone (accuracy 80%). In conclusion, this proof-of-concept study shows that a brief, self-administered digital cognitive test battery can detect cognitive impairment and, when combined with a blood test, accurately identify clinical AD in primary care.</p>}},
  author       = {{Tideman, Pontus and Karlsson, Linda and Strandberg, Olof and Calling, Susanna and Smith, Ruben and Midlöv, Patrik and Verghese, Philip B and Braunstein, Joel B and Mattsson-Carlgren, Niklas and Stomrud, Erik and Palmqvist, Sebastian and Hansson, Oskar}},
  issn         = {{1546-170X}},
  language     = {{eng}},
  month        = {{09}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Medicine}},
  title        = {{Primary care detection of Alzheimer's disease using a self-administered digital cognitive test and blood biomarkers}},
  url          = {{http://dx.doi.org/10.1038/s41591-025-03965-4}},
  doi          = {{10.1038/s41591-025-03965-4}},
  year         = {{2025}},
}