Improving methods to find the best time to treat neurodegenerative diseases
Developing a Robust and Efficient Strategy for Censored Covariates to Improve Clinical Trial Design for Neurodegenerative Diseases
This project builds better statistical tools to find when treatments will work best for people with neurodegenerative diseases such as Huntington disease.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of North Carolina Chapel Hill NIH-funded |
| Lab location | 1 site (Chapel Hill, United States) |
| Project ID | NIH-11330412 on NIH RePORTER |
What this research studies
Researchers are developing new statistical models to track how symptoms change before and after a clinical diagnosis when the exact diagnosis time is unknown. They will create methods that handle 'right-censored' diagnosis times—cases where a person’s diagnosis happens after the last study visit. The team will test these methods using existing longitudinal patient datasets and simulations to see how they change trial design decisions. Ultimately the work aims to help researchers pick the most helpful enrollment times and endpoints for future treatment studies.
Who could benefit from this research
Good fit: Ideal candidates are people with or at risk for degenerative neurologic disorders (for example Huntington disease) who have participated in long-term studies or trials and can share symptom and diagnosis-timing data.
Not a fit: People without neurodegenerative conditions or those who cannot provide or share longitudinal symptom data are unlikely to receive direct benefit from this work.
Why it matters
Potential benefit: If successful, this could make clinical trials more likely to detect treatments that slow or delay neurodegenerative diseases by choosing better times to intervene.
How similar studies have performed: Related statistical methods exist for some censored outcomes, but applying robust approaches to right-censored diagnosis timing in neurodegeneration is relatively new and not yet widely proven.
Where this research is happening
Chapel Hill, United States
- Univ of North Carolina Chapel Hill — Chapel Hill, United States (Active)
Researchers
- Principal investigator: Garcia, Tanya Pamela — Univ of North Carolina Chapel Hill
- Study coordinator: Garcia, Tanya Pamela
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 below.