Utilization of breast cancer risk prediction models by cancer genetic counselors in clinical practice predominantly in the United States.

Risk assessment in cancer genetic counseling is essential in identifying individuals at high risk for developing breast cancer to recommend appropriate screening and management options. Historically, many breast cancer risk prediction models were developed to calculate an individual's risk to develop breast cancer or to carry a pathogenic variant in the BRCA1 or BRCA2 genes. However, how or when genetic counselors use these models in clinical settings is currently unknown. We explored genetic counselors' breast cancer risk model usage patterns including frequency of use, reasons for using or not using models, and change in usage since the adoption of multi-gene panel testing. An online survey was developed and sent to members of the National Society of Genetic Counselors; board-certified genetic counselors whose practice included cancer genetic counseling were eligible to participate in the study. The response rate was estimated at 23% (243/1,058), and respondents were predominantly working in the United States. The results showed that 93% of all respondents use at least one breast cancer risk prediction model in their clinical practice. Among the six risk models selected for the study, the Tyrer-Cuzick (IBIS) model was used most frequently (95%), and the BOADICEA model was used least (40%). Determining increased or decreased surveillance and breast MRI eligibility were the two most common reasons for most model usage, while time consumption and difficulty in navigation were the two most common reasons for not using models. This study provides insight into perceived benefits and limitations of risk models in clinical use in the United States, which may be useful information for software developers, genetic counseling program curriculum developers, and currently practicing cancer genetic counselors.

Accuracy of Perceived Breast Cancer Risk in Black and White Women with an Elevated Risk.

Introduction: Perceived breast cancer risk predicts screening behaviors. However, perceived risk is often inaccurate, notably in Black women, who often underestimate their risk despite having higher disease-specific mortality rates. We examined predictors of perceived breast cancer risk, and its impact on surveillance. Methods: We used baseline data from a randomized trial targeting unaffected women recruited by relatives with early-onset breast cancer. Data collection occurred between 2012 and 2013. Accuracy of perceived risk was assessed by comparing perceived risk to objective lifetime breast cancer risks, calculated with the Gail and Claus models. A multivariate mixed model regression examined predictors of accuracy of perceived risk. The impact of perceived risk on breast cancer surveillance was assessed with one-way ANOVAS comparing Black to White women. Results: Among participants, 21.4% self-identified as Black and 78.6% as White. Overall, 72.9% (n=247/339), 16.2% (n=55/339), and 10.9% (n=37/339) of participants overestimated, accurately perceived, and underestimated, respectively, their lifetime breast cancer risk. Race did not predict the accuracy of risk perception. Younger participants were more likely to overestimate their risk (ß=-.455; CI [-.772, -.138]; P=.005). MRI utilization was predicted by a higher objective risk (F 1,263 [= 30.271]; P<.001) and more accurate risk perception (P=.010; Fisher's exact test). Conclusions: Most women with a family history of early-onset breast cancer inaccurately perceived their risk for developing the disease. Younger women were more likely to overestimate their risk. Findings can guide the development of tailored interventions to improve adherence to breast cancer surveillance recommendations.

Monoallelic MUTYH pathogenic variants ascertained via multi-gene hereditary cancer panels are not associated with colorectal, endometrial, or breast cancer.

We aimed to determine whether monoallelic MUTYH pathogenic and likely pathogenic variants (PVs) are associated with colorectal, breast, and endometrial cancer. Cases were individuals with colorectal, female breast, or endometrial cancer who reported European ancestry alone and underwent a multi-gene hereditary cancer panel at a large reference laboratory. Controls were individuals of European (non-Finnish) descent from GnomAD with cancer cohorts removed. We performed a Fisher's exact test to generate odds ratios (ORs) with 95% confidence intervals (CI). Prevalence of single MUTYH PVs in cancer cohorts versus controls, respectively, was: colorectal cancer, 2.1% vs. 1.8% (OR 1.2, 95% CI 0.99-1.5, p = 0.064); breast cancer 1.9% vs. 1.7% (OR 1.1, 95% CI 0.96-1.3, p = 0.15); and endometrial cancer, 1.7% vs. 1.7% (OR 0.98; 95% CI 0.70-1.3, p = 0.94). Using the largest colorectal and endometrial cancer cohorts and one of the largest breast cancer cohorts from a single case-control study, we did not observe a significant difference in the prevalence of monoallelic MUTYH PVs in these cohorts compared to controls. Additionally, frequencies among cancer cohorts were consistent with the published MUTYH carrier frequency of 1-2%. These findings suggest there is no association between colorectal, endometrial, or breast cancer and MUTYH heterozygosity in individuals of European ancestry.

Initial clinical validation of Health Heritage, a patient-facing tool for personal and family history collection and cancer risk assessment.

Personal and family health histories remain important independent risk factors for cancer; however they are currently not being well collected or used effectively. Health Heritage was designed to address this need. The purpose of this study was to validate the ability of Health Heritage to identify patients appropriate for further genetic evaluation and to accurately stratify cancer risk. A retrospective chart review was conducted on 100 random patients seen at an adult genetics clinic presenting with concern for an inherited predisposition to cancer. Relevant personal and family history obtained from the patients' medical records was entered into Health Heritage. Recommendations by Health Heritage were compared to national guidelines of eligibility for genetic evaluation. Agreement between Health Heritage referral for genetic evaluation and guideline eligibility for genetic evaluation was 97% (sensitivity 98% and specificity 88%). Risk stratification for cancer was also compared between Health Heritage and those documented by a geneticist. For patients at increased risk for breast, ovarian, or colorectal cancer as determined by the geneticist, risk stratification by Health Heritage agreed 90, 93, and 75%, respectively. Discordances in risk stratification were attributed to both complex situations better handled by the geneticist and Health Heritage's adherence to incorporating all information into its algorithms. Health Heritage is a clinically valid tool to identify patients appropriate for further genetic evaluation and to encourage them to confirm the assessment and management recommendations with cancer genetic experts. Health Heritage also provides an estimate of cancer risk that is complementary to a genetics team.