Breast Cancer Surveillance Consortium investigators received a $17 million program project grant renewal from NCI to study the effectiveness of different breast cancer screening and surveillance strategies using digital mammography, digital breast tomosynthesis, and breast MRI.
The consortium seeks to ensure that women get personalized care based on their individual risk and preferences. It is co-led by UC Davis researcher Diana Miglioretti.
Established in 1994, the BCSC is a nationwide research collaboration that includes UC San Francisco, the University of North Carolina, Geisel School of Medicine at Dartmouth, the University of Vermont, the University of Illinois, Advocate Health Care and Kaiser Permanente Washington. The consortium has a long history of evaluating the benefits and harms of different screening approaches.
The grant renewal expands on prior research by evaluating surveillance imaging of breast cancer survivors in addition to screening women without a history of breast cancer. BCSC research has helped fuel the shift from a one-size-fits-all screening approach to consideration of women’s breast cancer risk and preferences.
The ultimate goal is to tailor each woman’s screening regimen to her risk of screening outcomes based on family history, breast density and other risk factors, while also considering her personal preferences around balancing the potential benefits and harms of screening. Previous BCSC studies have been used to update the national breast cancer screening guidelines of the U.S. Preventive Services Task Force and the American Cancer Society.
The grant renewal will fund three projects to better match women with the most appropriate screening or surveillance regimens. For example, the consortium will investigate which women benefit most from tomosynthesis or breast MRI, and which will be better served by digital mammography alone.
They will investigate different ways to maximize early detection while minimizing failures and false alarms among all women receiving screening and among breast cancer survivors receiving surveillance for second breast cancer occurrences.
The ultimate goal is to develop a clinical algorithm that uses a woman’s information, such as personal and family history of breast cancer, race, age, breast density, history of breast biopsy and body mass index, to determine the ideal combination of imaging and other approaches to detect cancers early, when they are most treatable, while minimizing harms.
