Improving predictions and understanding of Alzheimer's disease progression
Official title: Statistical Methods for Accurate Estimation and Prediction in Alzheimer's Disease
Funded at New York University · NIH-11107569 · Data updated 2026-11-12
This study is working on new ways to better understand how Alzheimer's disease progresses over time, so that patients can get more accurate predictions about their condition and receive more effective treatments.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | New York University NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | May 15, 2025 |
| Project end | January 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $366,648 |
| NIH project number | 1R01AG092774-01 |
| Project ID | NIH-11107569 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals diagnosed with Alzheimer's disease or those at risk of developing it, particularly those involved in longitudinal studies.
✕Less likely to help
Patients with other forms of dementia or cognitive impairments unrelated to Alzheimer's disease may not benefit from this research.
What this research studies
This research focuses on developing advanced statistical methods to better estimate and predict the progression of Alzheimer's disease (AD) using data from longitudinal cohort studies. It addresses the challenges posed by complex data issues such as truncation and censoring, which can affect the accuracy of clinical trial designs and individual predictions. By creating more reliable models that account for these complexities, the research aims to enhance our understanding of AD progression and improve clinical trial outcomes. Patients may benefit from more accurate predictions regarding their condition and better-targeted interventions.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of Alzheimer's disease progression, improving patient care and treatment strategies.
How similar studies have gone: Previous research has shown promise in using advanced statistical methods for similar purposes, indicating a potential for success in this approach.
Where this research is happening
-
New York University
New York, United States Active
Researchers
- Principal investigator: Betensky, Rebecca a. — New York University
- Study coordinator: Betensky, Rebecca a.
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.