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Combining Cognitive Markers to Identify Individuals at Increased Dementia Risk: Influence of Modifying Factors and Time to Diagnosis
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI).ORCID iD: 0000-0002-0608-4124
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI).
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI).
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Number of Authors: 62020 (English)In: Journal of the International Neuropsychological Society, ISSN 1355-6177, E-ISSN 1469-7661, Vol. 26, no 8, p. 785-797, article id S1355617720000272Article in journal (Refereed) Published
Abstract [en]

Objective: We investigated the extent to which combining cognitive markers increases the predictive value for future dementia, when compared to individual markers. Furthermore, we examined whether predictivity of markers differed depending on a range of modifying factors and time to diagnosis. Method: Neuropsychological assessment was performed for 2357 participants (60þ years) without dementia from the population-based Swedish National Study on Aging and Care in Kungsholmen. In the main sample analyses, the outcome was dementia at 6 years. In the time-todiagnosis analyses, a subsample of 407 participants underwent cognitive testing 12, 6, and 3 years before diagnosis, with dementia diagnosis at the 12-year follow-up. Results: Category fluency was the strongest individual predictor of dementia 6 years before diagnosis [area under the curve (AUC) = .903]. The final model included tests of verbal fluency, episodic memory, and perceptual speed (AUC = .913); these three domains were found to be the most predictive across a range of different subgroups. Twelve years before diagnosis, pattern comparison (perceptual speed) was the strongest individual predictor (AUC = .686). However, models 12 years before diagnosis did not show significantly increased predictivity above that of the covariates. Conclusions: This study shows that combining markers from different cognitive domains leads to increased accuracy in predicting future dementia 6 years later. Markers from the verbal fluency, episodic memory, and perceptual speed domains consistently showed high predictivity across subgroups stratified by age, sex, education, apolipoprotein E ϵ4 status, and dementia type. Predictivity increased closer to diagnosis and showed highest accuracy up to 6 years before a dementia diagnosis.

Place, publisher, year, edition, pages
2020. Vol. 26, no 8, p. 785-797, article id S1355617720000272
Keywords [en]
Prediction, Preclinical dementia, Alzheimer's disease, Cognition, Population-based, Longitudinal
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:su:diva-186483DOI: 10.1017/S1355617720000272ISI: 000564883500005PubMedID: 32207675OAI: oai:DiVA.org:su-186483DiVA, id: diva2:1493973
Available from: 2020-11-04 Created: 2020-11-04 Last updated: 2022-02-25Bibliographically approved

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Payton, Nicola M.

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