Clinical Assessment of Breast Cancer Risk Based on Family History

Family history is a key component of breast cancer risk assessment. Family history provides clues as to the likelihood of a hereditary breast cancer syndrome and the need for a cancer genetics referral and can be used in the setting of a breast cancer risk assessment model to estimate a woman's risk. Appropriate breast cancer screening and risk reduction management plans rely on an accurate assessment of a patient's family history. This article reviews the NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Breast Cancer Risk Reduction and provides insight into the application of the guidelines in clinical practice.</jats:p

Validation of a digital identification tool for individuals at risk for hereditary cancer syndromes

Abstract Background The number of individuals meeting criteria for genetic counseling and testing for hereditary cancer syndromes (HCS) is far less than the number that actually receive it. To facilitate identification of patients at risk for HCS, Counsyl developed a digital identification tool (digital ID tool) to match personal and family cancer history to National Comprehensive Cancer Network (NCCN) BRCA-related Hereditary Breast and Ovarian Cancer (HBOC), Lynch syndrome, and polyposis testing criteria in one-to-one, automated fashion. The purpose of this study was to validate the ability of the digital ID tool to accurately identify histories that do and do not meet NCCN testing criteria. Methods Third-party recorded three-generation pedigrees were retrospectively reviewed by a certified genetic counselor (CGC) to determine if independent events included in pedigree histories met NCCN guidelines, and were then sorted into groups: high risk events (meets criteria) and low risk events (does not meet criteria). Events were entered into the digital ID tool to determine the extent of its concordance with events sorted by CGC review. Statistical tests of accuracy were calculated at a 95% confidence interval (CI). Results One hundred ninety-seven pedigrees were reviewed consecutively representing 765 independent events for analysis across groups. 382/382 (100%) high risk events identified by the digital ID tool and 381/383 (99.47%) low risk events identified by the digital ID tool were concordant with CGC sorting. The digital ID tool had a sensitivity of 100% (99.04–100% CI) and specificity of 99.48% (98.13–99.94% CI). The overall accuracy of the digital ID tool was estimated to be 99.74% (99.06–99.97% CI), reflecting the rate at which the digital ID tool reached the same conclusion as that of CGC review of pedigree events for the recommendation of genetic testing for individuals at risk for HCS. Conclusions The digital ID tool accurately matches NCCN criteria in one-to-one fashion to identify at-risk individuals for HCS and may be useful in clinical practice, specifically for BRCA-related HBOC and Lynch Syndrome

Clinical application of breast cancer risk assessment models

With the evolving availability of testing for genetic cancer syndromes, oncologists now are increasingly expected to review family histories and to give a genetic risk assessment as part of their care for breast cancer. The most important of these breast cancer genetic syndromes identified to date have been those associated with the BRCA1 and BRCA2 genes. Therefore, the proper identification of potentially affected families and providing risk assessment estimates will be ever more essential. This review outlines several different available breast cancer risk assessment models. Risk models for the development of breast cancer as well as risk models that estimate the chance of having a genetic cancer syndrome are discussed. Their clinical applications are also outlined and clinical situations appropriate for each model are reviewed. </jats:p

Additional file 1: of Validation of a digital identification tool for individuals at risk for hereditary cancer syndromes

Figure S1. Selected screenshots of Digital ID Tool as viewed on mobile device (as of February 2018). (PDF 2668 kb