Trial reportAlzheimer's & dementia : the journal of the Alzheimer's Association2025
Multimodal prognostic modeling of individual cognitive trajectories to enhance trial efficiency in preclinical Alzheimer's disease.
Trial report in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02008357 (Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease), which is not on this map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4 Study)
Who cites it
9 citing papers in PubMed.
- 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
- Advances in Primary Mitochondrial Diseases: Diagnosis, Natural History Studies and Clinical Trials.Genes · 2026Review
- Prognostic value of plasma %p-tau217 in cognitively unimpaired older adults.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Clinical pathways matter for multimodal deep learning in early Alzheimer's disease detection.Scientific reports · 2026Article
- EEG biomarkers can predict early-stage Alzheimer's disease and correlate with intracerebral pathology: a multimodal machine learning study.Alzheimer's research & therapy · 2026Article
- Circadian syndrome (CircS) and cognitive trajectory deterioration in middle-aged and older adults: A national cohort study with causal forest analysis.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Artificial intelligence and the acceleration of Alzheimer's research - From promise to practice.The journal of prevention of Alzheimer's disease · 2025Article
- Deep multimodal learning for domain-level cognitive decline prediction in Alzheimer's disease.Frontiers in artificial intelligence · 2025Article
- Review
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
introductionCognitive decline in asymptomatic preclinical Alzheimer's disease (AD) is slow and variable, limiting detection of treatment effects. This study developed models to forecast trajectories and improve trial efficiency.
methodsModels were trained on longitudinal Preclinical Alzheimer's Cognitive Composite (PACC) data up to 240 weeks from the Phase III A4 study of solanezumab. Baseline inputs included demographics, apolipoprotein E (APOE) ε4, clinical scores, amyloid positron emission tomography (PET), plasma pTau217, magnetic resonance imaging (MRI), and tau PET (sub-study). Stochastic gradient boosting was used, with evaluation via cross-validation and trial simulations.
resultsThe best model without tau PET used pTau217, clinical, and MRI data (R DISCUSSION: Prognostic models can predict decline in preclinical AD and improve trial efficiency. CLINICALTRIALS: GOV IDENTIFIERS: NCT02008357 (Clinical Trial of Solanezumab for Older Individuals Who May be at Risk for Memory Loss (A4)) HIGHLIGHTS: Models forecast 4.5-year cognitive decline in amyloid-positive preclinical Alzheimer's disease (AD). Plasma pTau217 and tau positron emission tomography (PET) standardized uptake value ratios (SUVRs) in early-accumulating regions are key predictors. Tau PET improves prediction beyond plasma, magnetic resonance imaging (MRI), and clinical measures. Forecasted decline as a prognostic covariate improves power and cuts sample size in trial simulations. Alternative models underperform yet retain practical utility when tau PET or pTau217 is unavailable.
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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.