Finding better ways to screen for gastric cancer in the US
Assessing feasibility of gastric cancer screening in the US
This study is looking at the best ways to find gastric cancer early in people who are at higher risk, like those with certain age, race, or family history, using advanced technology to help doctors identify who might need screening the most, so we can catch the disease sooner and improve survival rates, especially for different minority groups.
Quick facts
| Grant type | R37 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Cleveland Clinic Lerner Com-Cwru NIH-funded |
| Lab location | 1 site (Cleveland, United States) |
| Project ID | NIH-11108124 on NIH RePORTER |
What this research studies
This research investigates how to effectively screen for gastric cancer in the United States, particularly focusing on high-risk individuals rather than the general population. It aims to develop a targeted screening strategy using electronic health records and machine learning to identify those most likely to benefit from early detection. By understanding risk factors such as age, race, and family history, the study seeks to improve early diagnosis and ultimately enhance survival rates for gastric cancer patients. The research will also address disparities in gastric cancer incidence and mortality among different minority groups.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals with known risk factors for gastric cancer, such as older adults, those with a family history of the disease, and certain ethnic groups.
Not a fit: Patients who do not have any risk factors for gastric cancer or those already diagnosed with advanced gastric cancer may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier detection of gastric cancer, significantly improving survival rates and outcomes for patients.
How similar studies have performed: While similar screening approaches have been successful in other cancers, this specific application of machine learning and electronic health records for gastric cancer screening is relatively novel.
Where this research is happening
Cleveland, United States
- Cleveland Clinic Lerner Com-Cwru — Cleveland, United States (Active)
Researchers
- Principal investigator: Kim, Michelle Kang — Cleveland Clinic Lerner Com-Cwru
- Study coordinator: Kim, Michelle Kang
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.