Breast cancer remains the number one most common cancer among women in the United States, and the number two leading cause of cancer deaths among women.¹ Approximately 20% of all breast cancer cases are associated with a family history of breast cancer, and approximately 10% are hereditary (due to pathogenic variant or mutation in a gene).^2,3  

Despite these statistics, only a fraction of women who need increased screenings and/or genetic counseling and testing receive it. ³ With such clear needs, the establishment of high-risk breast programs is crucial.  

A high-risk breast program is designed to identify patients with an elevated risk of developing breast cancer and then offering genetic counseling, genetic testing, additional breast imaging, and risk-reduction strategies to mitigate their cancer risks. 

But where do you get started? 
  
First Things First: Envisioning Success 

A common question I often get asked is, “Where do I even start?” The answer is to envision what you want to accomplish with your high-risk program.  

• Define your goals. For instance, you may want to screen every patient in your breast imaging clinic and determine their breast cancer risk score. 

• Identify your target population. For example, your target population may be women with a clinical and/or family history of cancer who qualify for hereditary cancer testing and/or women who qualify for a breast MRI. 

• Envision how your program will operate. Where will screening occur, what screening tools will be used, and which teams and workflows are needed to support this program? 

• Establish what success would look like. Determine target metrics that will help you track the health and growth of your program. 

Then, begin by putting your ideas on paper; you don’t have to start at the beginning—you can fill in the gaps later. 

Up Next: Earning Buy-In 

Next, consider whose approval and buy-in you need to launch a program. Consider what justification they will want to see and who your key supporters and stakeholders will be. 

When I began assessing the need for a program, I used data to support my request and process. Examples of data that could be used include to support a high-risk program include: 

• 93% of female patients who qualify for high-risk breast MRI based on medical/family history do not have one.^4,5 

• 80% of people with BRCA-related Breast and/or Ovarian Cancer syndrome may not know it.⁶ 

• 1 in 279 people have Lynch syndrome, the most common hereditary cause of colorectal cancer.  >95% may not know it.^7,8< 

These metrics provided insight into the potential patient population that would be flagged as high-risk and would qualify for additional services within our system. 

Armed with this information, I was able to engage stakeholders and recruit a multidisciplinary team to support the program. 

Identifying the Right Tools and Partnerships 

Early on, we identified the need for comprehensive risk assessment that included hereditary cancer risk, not only the risk of breast cancer and need for increased breast surveillance. That meant that we would need to integrate genetic counseling and testing into our program in addition to breast imaging workflows. 

Operating in a busy breast imaging center with limited time per patient, our workflow focused on obtaining pertinent patient information in advance, evaluating it, determining their risk, and addressing high-risk patients and those eligible for genetic testing within our time constraints. 

One initial obstacle we encountered was compiling and documenting this information within an electronic health record accessible to team members, referring providers and intra-disciplinary support personnel. Fortunately, we partnered with Ambry Genetics, and my clinic was the first in our health system to launch a high-risk program using the Ambry CARE Program® (CARE). 

CARE leverages digital health tools to support: 

• Collection of patient and family cancer history before an appointment 

• Risk assessment (breast cancer risk score and qualification for hereditary cancer testing) 

• Ordering genetic testing and reviewing testing results 

• Providing patient education 

• Charting, tracking and sharing risk scores and test results 

• Referral to third-party telehealth genetic counselors at no cost 

Data, Data, Data! 

One of CARE's most significant contributions is supporting easier access to program data along with the ability to analyze it. 

Metrics are crucial for developing, sustaining and expanding a high-risk program. They measure growth and, most importantly, reflect downstream clinical value and return on investment (ROI), which is critical for facilitating stakeholder support. 

CARE can support access to many key metrics, including: 

• The proportion of patients that complete the risk assessment 

• Testing outcomes and testing turnaround times 

• Genetic counselor referral and patient volumes 

• Proportion of patients accessing digital education 

• Year-over-year program growth 

Other items to consider tracking: 

• Referral volumes and quality measures 

• Patient satisfaction scores 

• Provider satisfaction — both referring providers and specialty providers 

• Patient migration rates and any emerging patterns 

• Turning points for expansion and sustainability 

Presenting performance metrics to the C-suite and board members provides a distinct advantage. While opinions may differ, no one can dispute metrics reflecting hard facts. 

Internal data at our clinic revealed that with CARE, we assessed 89% of our breast imaging patients for breast and hereditary cancer risk. Of these, approximately 25% were identified as high-risk for breast cancer, and 11% met criteria for hereditary cancer testing. In one year, our clinic identified 584 patients with genetic mutations, providing education and referrals for increased screenings and risk-reducing strategies to each patient, impacting not only the patients but their family members as well. 

Conclusion 

Building a high-risk breast program demands strategic planning, collaboration, dedication to improving patient outcomes, and patience. As Mary-Claire King, PhD, aptly stated, "To identify a woman as a carrier only after she develops cancer is a failure of cancer prevention."

Watch the full interview:

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References: 

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2. Childers CP, Childers KK, Maggard-Gibbons M, Macinko J. National Estimates of Genetic Testing in Women With a History of Breast or Ovarian Cancer. J Clin Oncol. 2017 Dec 1;35(34):3800-3806. doi: 10.1200/JCO.2017.73.6314. Epub 2017 Aug 18. Erratum in: J Clin Oncol. 2018 Feb 1;36(4):432. PMID: 28820644; PMCID: PMC5707208. 

3. Engmann, N. J., Golmakani, M. K., Miglioretti, D. L., Sprague, B. L., Kerlikowske, K., & Breast Cancer Surveillance Consortium (2017). Population-Attributable Risk Proportion of Clinical Risk Factors for Breast Cancer. JAMA oncology, 3(9), 1228–1236. https://doi.org/10.1001/jamaoncol.2016.6326 

4. Miles R, Wan F, Onega TL, Lenderink-Carpenter A, O'Meara ES, Zhu W, Henderson LM, Haas JS, Hill DA, Tosteson ANA, Wernli KJ, Alford-Teaster J, Lee JM, Lehman CD, Lee CI. Underutilization of Supplemental Magnetic Resonance Imaging Screening Among Patients at High Breast Cancer Risk. J Womens Health (Larchmt). 2018 Jun;27(6):748-754. doi: 10.1089/jwh.2017.6623. Epub 2018 Jan 17. PMID: 29341851; PMCID: PMC6007803.  

5. Hill, D. A., Haas, J. S., Wellman, R., Hubbard, R. A., Lee, C. I., Alford-Teaster, J., Wernli, K. J., Henderson, L. M., Stout, N. K., Tosteson, A. N., Kerlikowske, K., & Onega, T. (2017). Utilization of breast cancer screening with Magnetic Resonance Imaging in Community practice. Journal of General Internal Medicine, 33(3), 275–283. https://doi.org/10.1007/s11606-017-4224-6 

6. Manickam, K., Buchanan, A. H., Schwartz, M. L. B., Hallquist, M. L. G., Williams, J. L., Rahm, A. K., Rocha, H., Savatt, J. M., Evans, A. E., Butry, L. M., Lazzeri, A. L., Lindbuchler, D. M., Flansburg, C. N., Leeming, R., Vogel, V. G., Lebo, M. S., Mason-Suares, H. M., Hoskinson, D. C., Abul-Husn, N. S., Dewey, F. E., … Murray, M. F. (2018). Exome Sequencing-Based Screening for BRCA1/2 Expected Pathogenic Variants Among Adult Biobank Participants. JAMA network open, 1(5), e182140. https://doi.org/10.1001/jamanetworkopen.2018.2140 

7. Win, A. K., Jenkins, M. A., Dowty, J. G., Antoniou, A. C., Lee, A., Giles, G. G., Buchanan, D. D., Clendenning, M., Rosty, C., Ahnen, D. J., Thibodeau, S. N., Casey, G., Gallinger, S., Le Marchand, L., Haile, R. W., Potter, J. D., Zheng, Y., Lindor, N. M., Newcomb, P. A., … MacInnis, R. J. (2017). Prevalence and penetrance of major genes and polygenes for colorectal cancer. Cancer Epidemiology, Biomarkers & Prevention, 26(3), 404–412. https://doi.org/10.1158/1055-9965.epi-16-0693   

8. Hampel H, de la Chapelle A. The search for unaffected individuals with Lynch syndrome: do the ends justify the means? Cancer Prev Res (Phila). 2011 Jan;4(1):1-5. doi: 10.1158/1940-6207.CAPR-10-0345. PMID: 21205737; PMCID: PMC3076593.