Mayo Clinic. US: A new breast cancer risk prediction model combining histologic features
of biopsied breast tissue from women with benign breast disease and
individual patient demographic information more accurately classified
breast cancer risk than the current screening standard. Results of a
Mayo Clinic study comparing the new model to the current standard, the Breast Cancer Risk Assessment Tool (BCRAT), are published in the Journal of Clinical Oncology.
“Physicians routinely perform biopsies to evaluate concerning
findings in the breast, either felt on exam or seen on mammogram, for
the presence of a breast cancer,” says Amy Degnim, M.D., a surgeon at
Mayo Clinic and a senior author of the study. “However, about
three-quarters of these biopsies prove to be benign and are referred to
as benign breast disease (BBD).” Annually, more than a million American
women have a biopsy with a benign finding and are left wondering if they
will later develop breast cancer.
Dr. Degnim and her colleagues hypothesized that certain breast tissue
findings, while benign, could help predict which women were at
increased risk of developing breast cancer later. “Our new model more
accurately classifies a woman’s breast cancer risk after a benign biopsy
than the BCRAT,” Dr. Degnim says. Developed by the National Cancer Institute and the National Surgical Adjuvant Breast and Bowel Project, BCRAT is currently the most commonly used model for predicting breast cancer risk in women with BBD.
To test the new model, Dr. Degnim and her colleagues studied a cohort
of approximately 10,000 women who had benign breast biopsies at Mayo
Clinic and who received long-term follow-up for a later breast cancer
occurrence. Using this cohort, researchers determined the age-specific
incidence of breast cancer and death, and combined these estimates with a
relative risk model derived from 377 patients who later developed
breast cancer and 734 matched controls sampled from the Mayo Clinic BBD
cohort. They validated the model using an independent set of women from
the Mayo BBD cohort (378 patients with a later breast cancer and 728
matched controls) and compared the risk predictions from the new model
with those from the BCRAT.
The concordance statistic from the new model was 0.665 in the model
development series and 0.629 in the validation series; these values were
higher than those from the BCRAT (0.567 and 0.472, respectively). The
BCRAT significantly underpredicted breast cancer risk after benign
biopsy (P .004), whereas predictions derived from the new model were appropriately calibrated to observed cancers (P .247).
“Since
women with benign breast disease are at higher risk for breast cancer,
optimal early detection is extremely important,” Dr. Degnim says.
“Ideally, women at increased risk for breast cancer should be identified
so that we can offer appropriate surveillance and prevention
strategies. Unfortunately, the BCRAT risk prediction model does not
provide accurate estimates of risk for these women at the individual
level.”
Co-authors include Lynn Hartmann, M.D., Ryan Frank, Marlene Frost, Ph.D., Daniel Visscher M.D., Robert Vierkant, Tina Hieken, M.D., Karthik Ghosh, M.D., Celine Vachon, Ph.D., and Derek Radisky, Ph.D., all of Mayo Clinic.
About Mayo Clinic Cancer Center
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Clinic Cancer Center conducts basic, clinical and population science
research, translating discoveries into improved methods for prevention,
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