Comparing ways to prevent, detect early, and treat lung cancer
Official title: Comparative Modeling of Lung Cancer Prevention, Early Detection and Treatment Interventions
Funded at Provincial Health Services Authority · NIH-10927292 · Data updated 2026-11-12
Computer models compare tobacco control, screening, and new treatments to find which strategies could best lower lung cancer for people who smoke or are at higher risk.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Provincial Health Services Authority NIH-funded |
| Lab location | 1 site (Vancouver, Canada) |
| Project start | December 3, 2022 |
| Project end | August 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $1,554,893 |
| NIH project number | 5U01CA253858-06 |
| Project ID | NIH-10927292 on NIH RePORTER |
Who could benefit from this research
✓Could help
People who currently smoke, former smokers, and others at higher risk of lung cancer (for example older adults with a history of smoking) are the main groups who could benefit from the results.
✕Less likely to help
People at very low risk for lung cancer, such as young never-smokers, are unlikely to see direct benefits from this modeling work.
What this research studies
From my perspective, researchers use large-scale computer models and national data to simulate how different tobacco control policies, screening programs, early detection methods, and treatment advances might change lung cancer cases and deaths. The work includes concerns about new products like e-cigarettes and looks at how prevention, early detection, and treatment could work together. This project uses existing public-health and clinical datasets rather than enrolling people in a clinical trial. Findings are meant to help guide policies and medical guidelines that affect people at risk for lung cancer.
Why it matters
Potential benefit: If successful, this could help shape policies and screening guidelines that reduce lung cancer deaths and improve early detection for people at risk.
How similar studies have gone: Previous CISNET modeling has successfully informed U.S. tobacco-control and lung cancer screening recommendations, so this project builds on established, influential modeling efforts.
Where this research is happening
-
Provincial Health Services Authority
Vancouver, Canada Active
Researchers
- Principal investigator: Meza, Rafael — Provincial Health Services Authority
- Study coordinator: Meza, Rafael
Related research
Other NIH-funded projects on the same topics.
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Blood-based markers to identify lung cancer risk in never-smokers
A researchers team at NYU School of Medicine is testing blood tests that might flag higher lung cancer risk in people who have never smoked, helping decide who might need screening.
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Integrative Analysis of Lung Cancer Risk and Its Causes
A large, multi-part study at the University of New Mexico is exploring why lung cancer happens and how to better prevent and detect it.
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Integrative Analysis of Lung Cancer Risk and Causes
A large NIH project is exploring how tobacco use, behavior, biology, and screening practices influence lung cancer risk and outcomes to help prevent and detect it earlier.
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Digital health strategies to expand lung cancer screening in safety-net clinics
A funded project aims to help low-resource clinics increase the use of lung cancer screening for patients who smoke or are at risk.
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Proteomics-guided matching of lung cancer tumors to preclinical models
This grant aims to improve how we match a patient’s lung cancer tumor to the right preclinical models using protein data.
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Optimizing lung cancer care with smart tools for prevention, early detection, treatment, and survivorship
A U01 grant using AI and biomarkers to improve lung cancer prevention, screening, treatment, and survivorship care for people at risk or living with lung cancer.
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.