ArticleJournal of Alzheimer's disease : JAD2018
Combining Cognitive, Genetic, and Structural Neuroimaging Markers to Identify Individuals with Increased Dementia Risk.
Article in Journal of Alzheimer's disease : JAD, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment.The Cochrane database of systematic reviews · 2020Pooled it
- Corpus callosum fractional anisotropy from routine diffusion tensor imaging predicts dementia in older adults beyond clinical risk factors.GeroScience · 2026Article
- Article
- Combinations of multimodal neuroimaging biomarkers and cognitive test scores to identify patients with cognitive impairment.Frontiers in aging neuroscience · 2025Article
- Article
- Early detection of dementia with default-mode network effective connectivity.Nature. Mental health · 2024Article
- A Machine Learning Approach for Early Diagnosis of Cognitive Impairment Using Population-Based Data.Journal of Alzheimer's disease : JAD · 2023Article
- Biomechanical response of the CNS is associated with frailty in NPH-suspected patients.Journal of neurology · 2020Article
- Cognitive, Genetic, Brain Volume, and Diffusion Tensor Imaging Markers as Early Indicators of Dementia.Journal of Alzheimer's disease : JAD · 2020Article
- Gray Matter Changes in Parkinson's and Alzheimer's Disease and Relation to Cognition.Current neurology and neuroscience reports · 2019Review
- What's New in Dementia Risk Prediction Modelling? An Updated Systematic Review.Dementia and geriatric cognitive disorders extraReview
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCognitive and biological markers have shown varying degrees of success in identifying persons who will develop dementia.
objectiveTo evaluate different combinations of cognitive and biological markers and identify prediction models with the highest accuracy for identifying persons with increased dementia risk.
methodsNeuropsychological assessment, genetic testing (apolipoprotein E -APOE), and structural magnetic resonance imaging (MRI) were performed for 418 older individuals without dementia (60-97 years) from a population-based study (SNAC-K). Participants were followed for six years.
resultsCognitive, genetic, and MRI markers were systematically combined to create prediction models for dementia at six years. The most predictive individual markers were perceptual speed or carrying at least one APOEɛ4 allele (AUC = 0.875). The most predictive model (AUC = 0.924) included variables from all three modalities (category fluency, general knowledge, any ɛ4 allele, hippocampal volume, white matter-hyperintensity volume).
conclusionThis study shows that combining markers within and between modalities leads to increased predictivity for future dementia. However, minor increases in predictive value should be weighed against the cost of additional tests in larger-scale screening.
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