cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders

Hanneke F M Rhodius-Meester; Teemu Paajanen; Juha Koikkalainen; Shadi Mahdiani; Marie Bruun; Marta Baroni; Afina W Lemstra; Philip Scheltens; Sanna-Kaisa Herukka; Maria Pikkarainen; Anette Hall; Tuomo Hänninen; Tiia Ngandu; Miia Kivipelto; Mark van Gils; Steen Gregers Hasselbalch; Patrizia Mecocci; Anne Remes; Hilkka Soininen; Wiesje M van der Flier; Jyrki Lötjönen

doi:10.1002/dad2.12083

cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders

Hanneke F M Rhodius-Meester (Corresponding Author), Teemu Paajanen, Juha Koikkalainen, Shadi Mahdiani, Marie Bruun, Marta Baroni, Afina W Lemstra, Philip Scheltens, Sanna-Kaisa Herukka, Maria Pikkarainen, Anette Hall, Tuomo Hänninen, Tiia Ngandu, Miia Kivipelto, Mark van Gils, Steen Gregers Hasselbalch, Patrizia Mecocci, Anne Remes, Hilkka Soininen, Wiesje M van der FlierJyrki Lötjönen

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Abstract

Introduction: Web-based cognitive tests have potential for standardized screening in neurodegenerative disorders. We examined accuracy and consistency of cCOG, a computerized cognitive tool, in detecting mild cognitive impairment (MCI) and dementia.

Methods: Clinical data of 306 cognitively normal, 120 mild cognitive impairment (MCI), and 69 dementia subjects from three European cohorts were analyzed. Global cognitive score was defined from standard neuropsychological tests and compared to the corresponding estimated score from the cCOG tool containing seven subtasks. The consistency of cCOG was assessed comparing measurements administered in clinical settings and in the home environment.Results: cCOG produced accuracies (receiver operating characteristic-area under the curve [ROC-AUC]) between 0.71 and 0.84 in detecting MCI and 0.86 and 0.94 in detecting dementia when administered at the clinic and at home. The accuracy was comparable to the results of standard neuropsychological tests (AUC 0.69-0.77 MCI/0.91-0.92 dementia).

Discussion: cCOG provides a promising tool for detecting MCI and dementia with potential for a cost-effective approach including home-based cognitive assessments.

Original language	English
Pages (from-to)	e12083
Journal	Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
Volume	12
Issue number	1
DOIs	https://doi.org/10.1002/dad2.12083
Publication status	Published - 2020
MoE publication type	A1 Journal article-refereed

Funding

Research of the Alzheimer Center Amsterdam is part of the neurodegeneration research program of Amsterdam Neuroscience. The Alzheimer Center Amsterdam is supported by Stichting Alzheimer Nederland and Stichting VUmc fonds. The clinical database structure was developed with funding from Stichting Dioraphte. For development of the PredictND tool, VTT Technical Research Centre of Finland received funding from European Union's Seventh Framework Programme for research, technological development, and demonstration under grant agreements 601055 (VPH-DARE@IT), 224328 (PredictAD), and 611005 (PredictND). The FINGER study was funded by Academy of Finland, Finnish Social Insurance Institution, Alzheimer's Research and Prevention Foundation, Juho Vainio Foundation; Swedish Research Council, Alzheimerfonden, Region Stockholm ALF and NSV, Center for Innovative Medicine (CIMED) at Karolinska Institutet, Knut and Alice Wallenberg Foundation, Stiftelsen Stockholms sjukhem; Joint Program of Neurodegenerative Disorders. The collaboration project DAILY (project number LSHM19123-HSGF) is co-funded by the PPP Allowance made available by Health-Holland, Top Sector Life Sciences & Health, to stimulate public-private partnerships. Wiesje M van der Flier holds the Pasman chair.

Keywords

Alzheimer's disease
clinical decision support
cognition
computerized cognitive test
dementia
memory
mild cognitive impairment
neuropsychology
web‐based cognitive test

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Rhodius-Meester, H. F. M., Paajanen, T., Koikkalainen, J., Mahdiani, S., Bruun, M., Baroni, M., Lemstra, A. W., Scheltens, P., Herukka, S.-K., Pikkarainen, M., Hall, A., Hänninen, T., Ngandu, T., Kivipelto, M., van Gils, M., Hasselbalch, S. G., Mecocci, P., Remes, A., Soininen, H., ... Lötjönen, J. (2020). cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders. Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring, 12(1), e12083. https://doi.org/10.1002/dad2.12083

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title = "cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders",

abstract = "Introduction: Web-based cognitive tests have potential for standardized screening in neurodegenerative disorders. We examined accuracy and consistency of cCOG, a computerized cognitive tool, in detecting mild cognitive impairment (MCI) and dementia.Methods: Clinical data of 306 cognitively normal, 120 mild cognitive impairment (MCI), and 69 dementia subjects from three European cohorts were analyzed. Global cognitive score was defined from standard neuropsychological tests and compared to the corresponding estimated score from the cCOG tool containing seven subtasks. The consistency of cCOG was assessed comparing measurements administered in clinical settings and in the home environment.Results: cCOG produced accuracies (receiver operating characteristic-area under the curve [ROC-AUC]) between 0.71 and 0.84 in detecting MCI and 0.86 and 0.94 in detecting dementia when administered at the clinic and at home. The accuracy was comparable to the results of standard neuropsychological tests (AUC 0.69-0.77 MCI/0.91-0.92 dementia).Discussion: cCOG provides a promising tool for detecting MCI and dementia with potential for a cost-effective approach including home-based cognitive assessments.",

keywords = "Alzheimer's disease, clinical decision support, cognition, computerized cognitive test, dementia, memory, mild cognitive impairment, neuropsychology, web‐based cognitive test",

author = "Rhodius-Meester, {Hanneke F M} and Teemu Paajanen and Juha Koikkalainen and Shadi Mahdiani and Marie Bruun and Marta Baroni and Lemstra, {Afina W} and Philip Scheltens and Sanna-Kaisa Herukka and Maria Pikkarainen and Anette Hall and Tuomo H{\"a}nninen and Tiia Ngandu and Miia Kivipelto and {van Gils}, Mark and Hasselbalch, {Steen Gregers} and Patrizia Mecocci and Anne Remes and Hilkka Soininen and {van der Flier}, {Wiesje M} and Jyrki L{\"o}tj{\"o}nen",

note = "Publisher Copyright: {\textcopyright} 2020 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association",

year = "2020",

doi = "10.1002/dad2.12083",

language = "English",

volume = "12",

pages = "e12083",

journal = "Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring",

issn = "2352-8729",

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Rhodius-Meester, HFM, Paajanen, T, Koikkalainen, J, Mahdiani, S, Bruun, M, Baroni, M, Lemstra, AW, Scheltens, P, Herukka, S-K, Pikkarainen, M, Hall, A, Hänninen, T, Ngandu, T, Kivipelto, M, van Gils, M, Hasselbalch, SG, Mecocci, P, Remes, A, Soininen, H, van der Flier, WM & Lötjönen, J 2020, 'cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders', Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring, vol. 12, no. 1, pp. e12083. https://doi.org/10.1002/dad2.12083

cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders. / Rhodius-Meester, Hanneke F M (Corresponding Author); Paajanen, Teemu; Koikkalainen, Juha et al.
In: Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring, Vol. 12, No. 1, 2020, p. e12083.

Research output: Contribution to journal › Article › Scientific › peer-review

TY - JOUR

T1 - cCOG

T2 - A web-based cognitive test tool for detecting neurodegenerative disorders

AU - Rhodius-Meester, Hanneke F M

AU - Paajanen, Teemu

AU - Koikkalainen, Juha

AU - Mahdiani, Shadi

AU - Bruun, Marie

AU - Baroni, Marta

AU - Lemstra, Afina W

AU - Scheltens, Philip

AU - Herukka, Sanna-Kaisa

AU - Pikkarainen, Maria

AU - Hall, Anette

AU - Hänninen, Tuomo

AU - Ngandu, Tiia

AU - Kivipelto, Miia

AU - van Gils, Mark

AU - Hasselbalch, Steen Gregers

AU - Mecocci, Patrizia

AU - Remes, Anne

AU - Soininen, Hilkka

AU - van der Flier, Wiesje M

AU - Lötjönen, Jyrki

PY - 2020

Y1 - 2020

N2 - Introduction: Web-based cognitive tests have potential for standardized screening in neurodegenerative disorders. We examined accuracy and consistency of cCOG, a computerized cognitive tool, in detecting mild cognitive impairment (MCI) and dementia.Methods: Clinical data of 306 cognitively normal, 120 mild cognitive impairment (MCI), and 69 dementia subjects from three European cohorts were analyzed. Global cognitive score was defined from standard neuropsychological tests and compared to the corresponding estimated score from the cCOG tool containing seven subtasks. The consistency of cCOG was assessed comparing measurements administered in clinical settings and in the home environment.Results: cCOG produced accuracies (receiver operating characteristic-area under the curve [ROC-AUC]) between 0.71 and 0.84 in detecting MCI and 0.86 and 0.94 in detecting dementia when administered at the clinic and at home. The accuracy was comparable to the results of standard neuropsychological tests (AUC 0.69-0.77 MCI/0.91-0.92 dementia).Discussion: cCOG provides a promising tool for detecting MCI and dementia with potential for a cost-effective approach including home-based cognitive assessments.

AB - Introduction: Web-based cognitive tests have potential for standardized screening in neurodegenerative disorders. We examined accuracy and consistency of cCOG, a computerized cognitive tool, in detecting mild cognitive impairment (MCI) and dementia.Methods: Clinical data of 306 cognitively normal, 120 mild cognitive impairment (MCI), and 69 dementia subjects from three European cohorts were analyzed. Global cognitive score was defined from standard neuropsychological tests and compared to the corresponding estimated score from the cCOG tool containing seven subtasks. The consistency of cCOG was assessed comparing measurements administered in clinical settings and in the home environment.Results: cCOG produced accuracies (receiver operating characteristic-area under the curve [ROC-AUC]) between 0.71 and 0.84 in detecting MCI and 0.86 and 0.94 in detecting dementia when administered at the clinic and at home. The accuracy was comparable to the results of standard neuropsychological tests (AUC 0.69-0.77 MCI/0.91-0.92 dementia).Discussion: cCOG provides a promising tool for detecting MCI and dementia with potential for a cost-effective approach including home-based cognitive assessments.

KW - Alzheimer's disease

KW - clinical decision support

KW - cognition

KW - computerized cognitive test

KW - dementia

KW - memory

KW - mild cognitive impairment

KW - neuropsychology

KW - web‐based cognitive test

UR - http://www.scopus.com/inward/record.url?scp=85100479471&partnerID=8YFLogxK

U2 - 10.1002/dad2.12083

DO - 10.1002/dad2.12083

M3 - Article

C2 - 32864411

SN - 2352-8729

VL - 12

SP - e12083

JO - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring

JF - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring

IS - 1

ER -

cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders

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