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PreprintCC BY-NC-NDmedRxiv

Diagnostic accuracy of remote self-administered digital cognitive assessment by clinical diagnosis and Alzheimer's disease PET imaging biomarkers

  • N. H. Stricker1
  • E. A. Boots
  • R. L. Taylor
  • W. Z. Fan
  • R. D. Frank
  • T. J. Christianson
  • J. L. Stricker1
  • W. K. Kremers
  • M. M. Machulda
  • P. A. Aduen
  • J. A. Lucas
  • M. A. Hughes
10 more authors
  • A. J. Karstens
  • G. S. Day
  • C. Lachner
  • N. R. Graff-Radford
  • J. Hassenstab
  • M. Mielke
  • , C. R. Jack
  • B. F. Boeve
  • J. Graff-Radford
  • R. C. Petersen
  1. 1Mayo Clinic
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Abstract

INTRODUCTIONCognitive characterization is increasingly important for Alzheimers disease treatment decisions, highlighting the need for scalable cognitive assessment. We evaluated the diagnostic accuracy of a remote self-administered cognitive screening battery, Mayo Test Drive (MTD), across clinically and biologically defined groups.

METHODSIn this prospectively designed study, 2,131 cognitively unimpaired (CU) and 118 cognitively impaired participants, including 96 with mild cognitive impairment and 22 with mild dementia (MCI/DEM), were recruited from observational cohort studies and completed MTD remotely (mean age=70 years, SD=12; 48% male; mean education=16 years, SD=2). Clinical diagnoses were determined by multidisciplinary consensus independently of MTD. Amyloid- and tau-PET were available for 1,224 participants. Logistic regression estimated associations between MTD and CU versus MCI/DEM, CU A-versus MCI/DEM A+, and A-T-versus A+T+. MTD diagnostic accuracy was compared with person-administered cognitive measures. Sensitivity and specificity across score types and comparison groups were examined.

RESULTSMTD showed excellent discrimination of CU versus MCI/DEM (AUC=.89; 95% CI=.87-.92), and discriminability remained high for CU versus MCI (AUC=.88; 95% CI=.85-.92). Discriminability was highest when comparing CU A- and MCI/DEM A+ groups (AUC=.95; 95% CI=.92-.97). MTD outperformed estimated MMSE (p=.02) and was comparable to Mayo-PACC (p=.71) for A-T-versus A+T+ discrimination (AUC=.76; 95% CI=.71-.81). Combining both raw score and normative score cutoffs helped balance sensitivity and specificity relative to use of either cutoff in isolation. A two-stage interpretation framework further improved sensitivity while maintaining clinically useful specificity and informed development of an interpretation guide.

DISCUSSIONA remote self-administered digital cognitive assessment showed strong diagnostic accuracy for detecting MCI and mild dementia in a large, primarily population-based cohort. The remote, self-administered MTD composite also showed comparable performance to established in-person cognitive composites for differentiating amyloid and tau-defined biomarker groups. Remote self-administered digital cognitive assessment may complement existing cognitive evaluation approaches and support scalable cognitive characterization.

HighlightsO_LIRemote self-administered cognitive assessment showed strong differentiation of cognitively unimpaired and cognitively impaired participants. C_LIO_LIDiagnostic accuracy improved when amyloid PET biomarker status was incorporated. C_LIO_LIRemote assessment demonstrated sensitivity to amyloid and tau PET-defined Alzheimers disease. C_LIO_LIPerformance was comparable to established in-person composites and better than an in-person mental status screening measure. C_LIO_LIDigital cognitive screening may support scalable treatment and clinical trial workflows. C_LI

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Cite

BibTeXRIS
BibTeX
@misc{stricker2026diagnostic,
  title = {{Diagnostic accuracy of remote self-administered digital cognitive assessment by clinical diagnosis and Alzheimer's disease PET imaging biomarkers}},
  author = {N. H. Stricker and E. A. Boots and R. L. Taylor and W. Z. Fan and R. D. Frank and T. J. Christianson and J. L. Stricker and W. K. Kremers and M. M. Machulda and P. A. Aduen and J. A. Lucas and M. A. Hughes and A. J. Karstens and G. S. Day and C. Lachner and N. R. Graff-Radford and J. Hassenstab and M. Mielke and , C. R. Jack and B. F. Boeve and J. Graff-Radford and R. C. Petersen},
  howpublished = {medRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.20.26362296},
  url = {https://www.medrxiv.org/content/10.64898/2026.09.20.26362296v1},
  note = {CC BY-NC-ND},
}
RIS
TY  - UNPB
TI  - Diagnostic accuracy of remote self-administered digital cognitive assessment by clinical diagnosis and Alzheimer's disease PET imaging biomarkers
AU  - N. H. Stricker
AU  - E. A. Boots
AU  - R. L. Taylor
AU  - W. Z. Fan
AU  - R. D. Frank
AU  - T. J. Christianson
AU  - J. L. Stricker
AU  - W. K. Kremers
AU  - M. M. Machulda
AU  - P. A. Aduen
AU  - J. A. Lucas
AU  - M. A. Hughes
AU  - A. J. Karstens
AU  - G. S. Day
AU  - C. Lachner
AU  - N. R. Graff-Radford
AU  - J. Hassenstab
AU  - M. Mielke
AU  - , C. R. Jack
AU  - B. F. Boeve
AU  - J. Graff-Radford
AU  - R. C. Petersen
PY  - 2026
DA  - 2026/09/20
PB  - medRxiv
DO  - 10.64898/2026.09.20.26362296
UR  - https://www.medrxiv.org/content/10.64898/2026.09.20.26362296v1
AB  - INTRODUCTIONCognitive characterization is increasingly important for Alzheimers disease treatment decisions, highlighting the need for scalable cognitive assessment. We evaluated the diagnostic accuracy of a remote self-administered cognitive screening battery, Mayo Test Drive (MTD), across clinically and biologically defined groups.  METHODSIn this prospectively designed study, 2,131 cognitively unimpaired (CU) and 118 cognitively impaired participants, including 96 with mild cognitive impairment and 22 with mild dementia (MCI/DEM), were recruited from observational cohort studies and completed MTD remotely (mean age=70 years, SD=12; 48% male; mean education=16 years, SD=2). Clinical diagnoses were determined by multidisciplinary consensus independently of MTD. Amyloid- and tau-PET were available for 1,224 participants. Logistic regression estimated associations between MTD and CU versus MCI/DEM, CU A-versus MCI/DEM A+, and A-T-versus A+T+. MTD diagnostic accuracy was compared with person-administered cognitive measures. Sensitivity and specificity across score types and comparison groups were examined.  RESULTSMTD showed excellent discrimination of CU versus MCI/DEM (AUC=.89; 95% CI=.87-.92), and discriminability remained high for CU versus MCI (AUC=.88; 95% CI=.85-.92). Discriminability was highest when comparing CU A- and MCI/DEM A+ groups (AUC=.95; 95% CI=.92-.97). MTD outperformed estimated MMSE (p=.02) and was comparable to Mayo-PACC (p=.71) for A-T-versus A+T+ discrimination (AUC=.76; 95% CI=.71-.81). Combining both raw score and normative score cutoffs helped balance sensitivity and specificity relative to use of either cutoff in isolation. A two-stage interpretation framework further improved sensitivity while maintaining clinically useful specificity and informed development of an interpretation guide.  DISCUSSIONA remote self-administered digital cognitive assessment showed strong diagnostic accuracy for detecting MCI and mild dementia in a large, primarily population-based cohort. The remote, self-administered MTD composite also showed comparable performance to established in-person cognitive composites for differentiating amyloid and tau-defined biomarker groups. Remote self-administered digital cognitive assessment may complement existing cognitive evaluation approaches and support scalable cognitive characterization.  HighlightsO_LIRemote self-administered cognitive assessment showed strong differentiation of cognitively unimpaired and cognitively impaired participants. C_LIO_LIDiagnostic accuracy improved when amyloid PET biomarker status was incorporated. C_LIO_LIRemote assessment demonstrated sensitivity to amyloid and tau PET-defined Alzheimers disease. C_LIO_LIPerformance was comparable to established in-person composites and better than an in-person mental status screening measure. C_LIO_LIDigital cognitive screening may support scalable treatment and clinical trial workflows. C_LI
ER  -