ArticleAlzheimer's research & therapy2019
Prediction models for dementia and neuropathology in the oldest old: the Vantaa 85+ cohort study.
Article in Alzheimer's research & therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed, 56 citations in OpenAlex.
- Association of comorbid depressive and anxiety symptoms with cognitive impairment and dementia in Chinese elderly people.BMC psychiatry · 2026Article
- Neuropathological Heterogeneity of Dementia Due to Combined Pathology in Aged Patients: Clinicopathological Findings in the Vallecas Alzheimer's Reina Sofía Cohort.Journal of clinical medicine · 2024Article
- Adiponectin and Inflammatory Marker Levels in the Elderly Patients with Diabetes, Mild Cognitive Impairment and Depressive Symptoms.International journal of molecular sciences · 2024Article
- Comparison of subjective cognitive decline and polygenic risk score in the prediction of all-cause dementia, Alzheimer's disease and vascular dementia.Alzheimer's research & therapy · 2024Article
- Neuropathologic Burden and Dementia in Nonagenarians and Centenarians: Comparison of 2 Community-Based CohortsNeurology · 2024Article
- Loss of TDP-43 splicing repression occurs early in the aging population and is associated with Alzheimer's disease neuropathologic changes and cognitive decline.Acta neuropathologica · 2023Article
- Using Hypothesis-Led Machine Learning and Hierarchical Cluster Analysis to Identify Disease Pathways Prior to Dementia: Longitudinal Cohort Study.Journal of medical Internet research · 2023Article
- Prediction of neuropathologic lesions from clinical data.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023Article
- Mid- and later-life risk factors for predicting neuropathological brain changes associated with Alzheimer's and vascular dementia: The Honolulu Asia Aging Study and the Age, Gene/Environment Susceptibility-Reykjavik Study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023Article
- Assessment of Alzheimer-related pathologies of dementia using machine learning feature selection.Alzheimer's research & therapy · 2023Article
- Article
- External validation of existing dementia prediction models on observational health data.BMC medical research methodology · 2022Review
- Preclinical Alzheimer's dementia: a useful concept or another dead end?European journal of ageing · 2022Review
- Apolipoprotein E Genotype e2: Neuroprotection and Its Limits.Frontiers in aging neuroscience · 2022Review
- Repurposing food molecules as a potential BACE1 inhibitor for Alzheimer's disease.Frontiers in aging neuroscience · 2022Article
- MRI-based machine learning model: A potential modality for predicting cognitive dysfunction in patients with type 2 diabetes mellitus.Frontiers in bioengineering and biotechnology · 2022Article
- Derivation and Validation of the Cognitive Impairment Prediction Model in Older Adults: A National Cohort Study.Frontiers in aging neuroscience · 2022Article
- A Comprehensive Machine Learning Framework for the Exact Prediction of the Age of Onset in Familial and Sporadic Alzheimer's Disease.Diagnostics (Basel, Switzerland) · 2021Article
- Predicting amyloid positivity in patients with mild cognitive impairment using a radiomics approach.Scientific reports · 2021Article
- A Risk Prediction Model Based on Machine Learning for Cognitive Impairment Among Chinese Community-Dwelling Elderly People With Normal Cognition: Development and Validation Study.Journal of medical Internet research · 2021Article
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Authors and funding
15 authors at 6 institutions in 3 countries.
Funding
Abstract
backgroundWe developed multifactorial models for predicting incident dementia and brain pathology in the oldest old using the Vantaa 85+ cohort.
methodsWe included participants without dementia at baseline and at least 2 years of follow-up (N = 245) for dementia prediction or with autopsy data (N = 163) for pathology. A supervised machine learning method was used for model development, considering sociodemographic, cognitive, clinical, vascular, and lifestyle factors, as well as APOE genotype. Neuropathological assessments included β-amyloid, neurofibrillary tangles and neuritic plaques, cerebral amyloid angiopathy (CAA), macro- and microscopic infarcts, α-synuclein pathology, hippocampal sclerosis, and TDP-43.
resultsPrediction model performance was evaluated using AUC for 10 × 10-fold cross-validation. Overall AUCs were 0.73 for dementia, 0.64-0.68 for Alzheimer's disease (AD)- or amyloid-related pathologies, 0.72 for macroinfarcts, and 0.61 for microinfarcts. Predictors for dementia were different from those in previous reports of younger populations; for example, age, sex, and vascular and lifestyle factors were not predictive. Predictors for dementia versus pathology were also different, because cognition and education predicted dementia but not AD- or amyloid-related pathologies. APOE genotype was most consistently present across all models. APOE alleles had a different impact: ε4 did not predict dementia, but it did predict all AD- or amyloid-related pathologies; ε2 predicted dementia, but it was protective against amyloid and neuropathological AD; and ε3ε3 was protective against dementia, neurofibrillary tangles, and CAA. Very few other factors were predictive of pathology.
conclusionsDifferences between predictors for dementia in younger old versus oldest old populations, as well as for dementia versus pathology, should be considered more carefully in future studies.
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