Karla Kerlikowske
University of California-Davis, CA·Medicine & Clinical Research
Screening mammograms lower breast cancer deaths mainly by catching cancers before they become advanced. Still, about 22% of regularly screened women who get breast cancer are diagnosed at an advanced stage.
- Fields
Medicine & Clinical Research
Public Health & Epidemiology
Mathematics & Statistics
- Topics
breast cancer
screening mammography
risk prediction
- Grants
- 1 known grant, through May 2027
What they work on
- Develop and validate models that predict a woman's 6-year risk of advanced breast cancer, combining clinical risk factors, race and ethnicity, imaging features and AI output in Breast Cancer Surveillance Consortium data, and test their fairness across racial and ethnic groups.
- Compare yearly and every-other-year mammography for their effect on breast cancer deaths at different levels of advanced cancer risk, by statistically emulating a randomized trial within a causal inference framework.
- Estimate the long-term benefits and harms of screening strategies that set mammography frequency and add MRI based on advanced cancer risk, using three established breast cancer simulation models.
- Determine whether risk-based screening improves outcomes compared with age-based screening, weighing deaths averted and life-years gained against false positives and biopsies.
More about the research
Among Black women, the rate of advanced cancer is more than twice the rate among White women. The team treats the advanced cancer rate as a key screening outcome because it best identifies who is most likely to die of breast cancer. If high-risk women can be identified and screened more effectively, fewer may die. Low-risk women might be screened less often and avoid unnecessary harms.
Why it matters
Advanced breast cancer is more common in some groups of women, including more than twice as common in Black women as in White women. Tools that predict advanced cancer risk could help women and their doctors choose how often to screen and whether to add MRI. Findings could also inform national screening guidelines, aiming for fair strategies that prevent more breast cancer deaths while limiting false positives and unneeded biopsies.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Christoph Lee
University of Wisconsin-Madison, WI·Medicine & Clinical Research
Validate a 2D mammography AI algorithm from the DREAM Digital Mammography Challenge on UCLA's Athena Breast Health Network registry, and refine it with radiologist supervision plus genetic mutation and tumor subtype data.
Jennifer Lund
University of North Carolina at Chapel Hill, NC·Public Health & Epidemiology
Estimate the real-world benefits and harms of low-dose CT lung cancer screening among people eligible for screening, using trial transport to adjust National Lung Screening Trial results to national survey populations.
Sarah Robertson
Dartmouth College, NH·Public Health & Epidemiology·Early-career
Transport the effects of lung cancer screening strategies from trials such as NLST to nationally representative target populations by combining information from claims, registries, and studies.
The school
University of California-Davis: 49 labs on PI Pages, $1.0B a year on research, 647 research doctorates a year.
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