Finding better ways to identify markers for diabetes treatment effectiveness
Robust Statistical Methods to Identify and Use Surrogate Markers in Diabetes
This study is looking at better ways to use certain indicators to help doctors make faster and smarter decisions about diabetes treatments, so that patients can get more personalized care that works best for them.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Texas at Austin NIH-funded |
| Lab location | 1 site (Austin, United States) |
| Project ID | NIH-10878572 on NIH RePORTER |
What this research studies
This research focuses on improving the identification and use of surrogate markers in diabetes treatment, which can help in making quicker decisions about the effectiveness of interventions. By developing robust statistical methods, the project aims to address the challenges faced in evaluating these markers, particularly for different patient subgroups defined by various characteristics. This approach could lead to more personalized and effective diabetes management strategies, ultimately improving patient outcomes.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals diagnosed with diabetes who may benefit from improved treatment strategies.
Not a fit: Patients without a diabetes diagnosis or those who do not have access to diabetes treatment options may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to faster and more accurate assessments of diabetes treatments, enhancing patient care and outcomes.
How similar studies have performed: Previous research has shown promise in using surrogate markers for other chronic diseases, suggesting that this approach could be beneficial for diabetes as well.
Where this research is happening
Austin, United States
- University of Texas at Austin — Austin, United States (Active)
Researchers
- Principal investigator: Parast, Layla — University of Texas at Austin
- Study coordinator: Parast, Layla
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.