Family history-based models work better than non-family-based models

Mary Beth Terry, PhD, a professor at Columbia University's Mailman School of Public Health, evaluated four commonly used bad cancer prediction models and found that family history models outperformed models not based on family history, even for women with a risk of bad cancer average or below average. The study is the largest independent badysis to validate four widely used models of bad cancer risk and has the longest prospective follow-up data available to date. The results are published online in Lancet Oncology.

Dr. Terry and her colleagues used the Breast Cancer Prospective Family Studies cohort of 18,856 Australian, Canadian, and US non-bad cancer women between March 1992 and June 2011. Women aged 20 to 18 at age 70 were selected to participate in the study. had no history of bilateral prophylactic mastectomy or ovarian cancer and whose family history of bad cancer was available. The researchers calculated the 10-year risk scores for the last cohort of 15,732 women, comparing four bad cancer risk models, all of which vary in how they use multigenerational and genetic information, as well as information. non-genetic: bad and ovarian badysis. of the disease and carrier incidence estimation algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT) and the International Study Model for bad cancer intervention (IBIS). A second badysis was performed to compare the performance of the models after 10 years on the basis of mutation status of the BRCA1 or BRCA2 genes.

The results showed that the BOADICIA and IBIS models, which contain data on multigenerational family history, more accurately predicted the risk of bad cancer than other models. This is true even for women with no family history of bad and without BRCA1 and BRCA2 mutations. The other two models, the BRCAPRO and BCRAT models, have not been as good overall and among women under 50. The BCRAT model was well calibrated in women over 50 who were not known to carry deleterious mutations in the BRCA1 and BRCA2 genes. Breast cancer was diagnosed in 4% of the 15,732 eligible women during the median follow-up of more than 11 years.

"Our study, enriched by family history, was broad enough to badess model performance across the entire spectrum of absolute risk, including women with the highest risk of cancer for whom accurate prediction is particularly important." said Dr. Terry, who is professor of epidemiology at the Columbia Mailman School and the Herbert Irving Comprehensive Cancer Center. "Independent validation is particularly important to understand the utility of these models in different contexts."

Breast cancer risk models are used to inform decisions about primary prevention and, increasingly, screening programs, including when women should have mammograms. There are different models for badessing the risk of bad cancer and how they take into account family history and genetics varies.

"Mathematical models can help estimate the future risk of a woman's bad cancer, there are many, but we do not know which models are the most appropriate." These results could help better guide women in their lives. decision-making on bad cancer screening strategies, "said Dr. Robert MacInnis, senior researcher at the Division of Cancer Epidemiology and Cancer Intelligence at the Cancer Council in Victoria, Australia, and led the badyzes with Dr. Terry.

"Our findings suggest that all women would benefit from a risk badessment involving the collection of detailed family histories and that risk models would be improved by including information on family history, including age. of the diagnosis and types of cancer, "said Dr. Terry.