Tailoring breast screening by individual risk and cost
Project 4: CISNET Modeling of outcomes and cost for risk-based screening strategies
This project uses computer simulations to compare personalized breast screening plans with standard guideline recommendations for women of different ages, breast density, and risk levels.
Quick facts
| Grant type | P01 program project |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project ID | NIH-11191512 on NIH RePORTER |
What this research studies
From my point of view as someone thinking about breast cancer screening, researchers will use a well-established simulation model (MISCAN-Fadia) to project long-term outcomes for different screening approaches. They will feed the model with data from trials like WISDOM and other high-quality sources and use new subtype-specific risk models developed elsewhere in the grant to set risk thresholds. The simulations will estimate benefits, harms, and costs for personalized screening versus three commonly used US guideline strategies (ACR, ACS, USPSTF) across groups defined by age, breast density, comorbidity, race, and other risk factors. Because breast cancer can take many years to develop, these kinds of models help predict long-term effects without requiring decades of new trials.
Who could benefit from this research
Good fit: This work is most relevant to adult women concerned about breast cancer risk, including those with dense breasts or known risk factor profiles, because the models represent these subgroups.
Not a fit: People whose circumstances are not represented in the modeled data (for example very rare genetic conditions or populations not included in source datasets) may not see direct benefit from the results.
Why it matters
Potential benefit: If successful, the work could lead to screening recommendations that find more cancers early while reducing unnecessary tests and costs.
How similar studies have performed: CISNET models like MISCAN-Fadia have previously informed national screening guidance, though applying subtype-specific personalized strategies at the population level is newer.
Where this research is happening
San Francisco, United States
- University of California, San Francisco — San Francisco, United States (Active)
Researchers
- Principal investigator: Tice, Jeffrey a — University of California, San Francisco
- Study coordinator: Tice, Jeffrey a
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.