Observational studyCPT: pharmacometrics & systems pharmacology2023
Modeling Alzheimer's disease progression utilizing clinical trial and ADNI data to predict longitudinal trajectory of CDR-SB.
Observational study in CPT: pharmacometrics & systems pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Characterizing Clinical Progression in Cognitively Unimpaired Older Individuals with Brain Amyloid: Results from the A4 Study.The journal of prevention of Alzheimer's disease · 2024Trial
- Identifying sex-specific sub-phenotypes of Alzheimer's disease progression using longitudinal electronic health records.EBioMedicine · 2026Article
- Empowering Clinical Development With Disease Progression Modeling: Recommendations From the Clinical Trials Transformation Initiative.Clinical and translational science · 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
- Predicting rates of cognitive and functional decline in Alzheimer's disease and mild cognitive impairment.Communications medicine · 2026Article
- Cerebrospinal Fluid CCL25 as a Biomarker for Alzheimer's Disease: Associations with Pathology, Neurodegeneration, and Cognitive Decline.Molecular neurobiology · 2025Article
- APOE4 genotypes and the trajectory of biomarkers, neuroimaging, and cognitive measures in Alzheimer's Disease: A mixed-effects disease progression model.Journal of pharmacokinetics and pharmacodynamics · 2025Article
- Identifying Sex-Specific Sub-phenotypes of Alzheimer's Disease Progression Using Longitudinal Electronic Health Records.medRxiv : the preprint server for health sciences · 2025Article
- Failure to recover from proactive semantic interference predicts trajectory of decline in everyday function among older adults with amnestic mild cognitive impairment.International psychogeriatrics · 2025Article
- Deep learning to predict rapid progression of Alzheimer's disease from pooled clinical trials: A retrospective study.PLOS digital health · 2024Article
- Advancing the utilization of real-world data and real-world evidence in clinical pharmacology and translational research-Proceedings from the ASCPT 2023 preconference workshop.Clinical and translational science · 2024Review
- Modeling Alzheimer's disease progression utilizing clinical trial and ADNI data to predict longitudinal trajectory of CDR-SB.CPT: pharmacometrics & systems pharmacology · 2023Observational
- Simulation of long-term lecanemab treatment effect on Alzheimer's disease progression.Alzheimer's & dementia (New York, N. Y.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
There is strong interest in developing predictive models to better understand individual heterogeneity and disease progression in Alzheimer's disease (AD). We have built upon previous longitudinal AD progression models, using a nonlinear, mixed-effect modeling approach to predict Clinical Dementia Rating Scale - Sum of Boxes (CDR-SB) progression. Data from the Alzheimer's Disease Neuroimaging Initiative (observational study) and placebo arms from four interventional trials (N = 1093) were used for model building. The placebo arms from two additional interventional trials (N = 805) were used for external model validation. In this modeling framework, CDR-SB progression over the disease trajectory timescale was obtained for each participant by estimating disease onset time (DOT). Disease progression following DOT was described by both global progression rate (RATE) and individual progression rate (α). Baseline Mini-Mental State Examination and CDR-SB scores described the interindividual variabilities in DOT and α well. This model successfully predicted outcomes in the external validation datasets, supporting its suitability for prospective prediction and use in design of future trials. By predicting individual participants' disease progression trajectories using baseline characteristics and comparing these against the observed responses to new agents, the model can help assess treatment effects and support decision making for future trials.
Indexed as
Identifiers
What OpenQuestion holds
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.