Improving survival analysis for cancer treatments using advanced statistical methods
Official title: Sieve based full likelihood approach for the Cox proportional hazards model with applications to immunotherapies trials
Funded at Duke University · NIH-10793642 · Data updated 2026-11-12
This study is looking at better ways to analyze survival data from cancer treatments, especially when there aren't many patients involved, to help make sure new immunotherapies are tested more accurately and effectively for everyone.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Duke University NIH-funded |
| Lab location | 1 site (Durham, United States) |
| Project start | February 22, 2023 |
| Project end | January 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $178,760 |
| NIH project number | 5R21CA263950-02 |
| Project ID | NIH-10793642 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients participating in clinical trials for cancer treatments, particularly those receiving immunotherapy.
✕Less likely to help
Patients not involved in clinical trials or those receiving standard treatments without immunotherapy may not benefit from this research.
What this research studies
This research focuses on enhancing the analysis of survival data in clinical trials, particularly for cancer treatments where traditional methods may fall short due to small sample sizes. By employing a sieve-based full likelihood approach to the Cox proportional hazards model, the study aims to provide more reliable results in evaluating the efficacy of immunotherapies. The methodology seeks to adjust for confounding factors and improve statistical power, ultimately benefiting the assessment of new cancer treatments. The findings and tools developed will be made publicly available to aid in future clinical studies.
Why it matters
Potential benefit: If successful, this research could lead to more accurate evaluations of cancer treatments, improving patient outcomes through better-informed clinical decisions.
How similar studies have gone: Previous research has shown that advanced statistical methods can significantly enhance the reliability of survival analysis in clinical trials, indicating a promising approach in this area.
Where this research is happening
-
Duke University
Durham, United States Active
Researchers
- Principal investigator: Wu, Yuan — Duke University
- Study coordinator: Wu, Yuan
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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.