Developing new methods to predict cancer outcomes and improve opioid prescription guidelines
New Statistical Methods for Modelling Cancer Outcomes
This study is looking at new ways to help doctors predict how cancer patients will do after surgery and to improve how they prescribe pain medication, all while keeping patients safe from addiction, and it also wants to find out how lung strength affects survival in lung cancer patients to create better treatment plans just for them.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Michigan at Ann Arbor NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project ID | NIH-11124295 on NIH RePORTER |
What this research studies
This research focuses on creating advanced statistical methods to better predict outcomes for cancer patients and improve opioid prescription practices. By analyzing large databases of surgical patients, the study aims to establish data-driven guidelines that can help manage pain effectively while minimizing the risk of addiction. Additionally, it explores the relationship between lung muscle metrics and lung cancer mortality, which could lead to personalized treatment strategies for patients. The approach combines clinical data with innovative modeling techniques to enhance patient care.
Who could benefit from this research
Good fit: Ideal candidates for this research include adult patients undergoing surgery for cancer who are opioid-naïve and may benefit from tailored pain management strategies.
Not a fit: Patients who are not undergoing surgery or those who are already receiving opioid treatment may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to safer opioid prescribing practices and improved survival rates for cancer patients.
How similar studies have performed: Previous research has shown promise in using statistical modeling to improve patient outcomes, indicating that this approach could be effective.
Where this research is happening
Ann Arbor, United States
- University of Michigan at Ann Arbor — Ann Arbor, United States (Active)
Researchers
- Principal investigator: Li, Yi — University of Michigan at Ann Arbor
- Study coordinator: Li, Yi
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.