ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2024
Predicting clinical progression trajectories of early Alzheimer's disease patients.
Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 27 citations in OpenAlex.
- Multimodal prognostic modeling of individual cognitive trajectories to enhance trial efficiency in preclinical Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Trial
- Enhancing early Alzheimer's disease clinical trials through prognostic score covariate adjustment.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Quantifying generalization error in machine learning prediction of cognitive decline.The journal of prevention of Alzheimer's disease · 2026Article
- Biomarker-Conditioned Vision Transformers with Deformable Biomarker Attention for Alzheimer's Disease Classification.Journal of imaging informatics in medicine · 2026Article
- Multimodal MRI combined with RNA sequencing reveals pathological signatures in the 9-month-old 3×Tg-AD mouse brain.Neural regeneration research · 2026Article
- Combining plasma biomarkers and cognitive challenge tests enhances prediction of functional trajectories of decline among older adults with cognitive impairment.Journal of Alzheimer's disease : JAD · 2026Article
- Clinical impact of the Alzheimer's Disease Neuroimaging Initiative: A review of studies using ADNI data (2023 to June 2025).Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Review
- Machine-learning prediction and risk stratification of 12-month cognitive decline in Alzheimer's disease using routine clinical and MRI data.Scientific reports · 2026Article
- Predicting rates of cognitive and functional decline in Alzheimer's disease and mild cognitive impairment.Communications medicine · 2026Article
- Integrating standard and native spaces for radiomics and brain network analysis in Alzheimer's disease diagnosis and prognosis.Journal of neurology · 2026Article
- Investigating the Amyloid-Tau-Neurodegeneration Framework in Alzheimer's Disease Using Semi-Supervised Multimodal Imaging Data Fusion.medRxiv : the preprint server for health sciences · 2025Article
- Tau-Clinical Mismatch Identifies Individuals with Co-Pathology and Predicts Clinical Trajectory.medRxiv : the preprint server for health sciences · 2025Article
- Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study.Journal of medical Internet research · 2025Article
- Predicted natural progression as an Alzheimer's prognostic covariate improves the precision of lecanemab efficacy assessments and clinical trial efficiency.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Studying Alzheimer's disease through an integrative serum metabolomic and lipoproteomic approach.Journal of translational medicine · 2025Article
- Deep multimodal learning for domain-level cognitive decline prediction in Alzheimer's disease.Frontiers in artificial intelligence · 2025Article
- Structural and microstructural changes in white and gray matter across the Alzheimer's disease continuum.Frontiers in aging neuroscience · 2025Review
- Predicting Cognitive Decline in Amyloid-Positive Patients With Mild Cognitive Impairment or Mild Dementia.Neurology · 2024Article
- Plasma pTau217 predicts continuous brain amyloid levels in preclinical and early Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Predicting clinical progression trajectories of early Alzheimer's disease patients.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundModels for forecasting individual clinical progression trajectories in early Alzheimer's disease (AD) are needed for optimizing clinical studies and patient monitoring.
methodsPrediction models were constructed using a clinical trial training cohort (TC; n = 934) via a gradient boosting algorithm and then evaluated in two validation cohorts (VC 1, n = 235; VC 2, n = 421). Model inputs included baseline clinical features (cognitive function assessments, APOE ε4 status, and demographics) and brain magnetic resonance imaging (MRI) measures.
resultsThe model using clinical features achieved R DISCUSSION: Our validated prediction models enable baseline prediction of clinical progression trajectories in early AD, benefiting clinical trial enrichment and various applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.