Breast cancer, a complex and heterogeneous disease, is the most common malignancy diagnosed in women in the United States, with over 180,000 new cases and approximately 44,000 deaths per year. Breast cancer risk is influenced by a large number of factors, including age, family history, reproductive and hormonal history, proliferative breast conditions, physical activity, diet, and environmental exposures. These factors all interact in a complex manner to contribute to the risk of developing breast cancer. Because the interactions between risk factors are poorly understood at the molecular level, it is difficult to accurately evaluate the breast cancer risk of a given person presenting with an individual constellation of factors. To better define the population at increased risk that may warrant specific intervention, several models exist to estimate a woman's risk for developing breast cancer and for harboring a germline mutation in a cancer susceptibility gene. This article summarizes these models and gives brief guidelines about which model may be preferable given a specific family history.
Breast Cancer Risk Assessment: A Guide for Clinicians Using the NCCN Breast Cancer Risk Reduction Guidelines
Sofia D. Merajver and Kara Milliron
BPI20-008: Pilot Testing of InheRET™, an Online Tool to Facilitate NCCN Guideline®-Compliant Referrals for Cancer Genetic Counseling and Increase Access to Care
Amanda M. Cook, David F. Keren, Lynn McCain, Lee F. Schroeder, Kara Milliron, Sofia Merajver, Diane Harper, Philip Zazove, Janice Farrehi, Susan Ernst, and Jasmine Parvaz
Implementation of INHERET, an Online Family History and Cancer Risk Interpretation Program for Primary Care and Specialty Clinics
Lynn A. McCain, Kara J. Milliron, Amanda M. Cook, Robert Paquette, Jasmine B. Parvaz, Susan D. Ernst, Anne L. Kittendorf, Diane M. Harper, Philip Zazove, Jim Arthurs, Jerry A. Tippie, Bailey Hulswit, Lee F. Schroeder, David F. Keren, and Sofia D. Merajver
Background: Individuals at increased risk for cancer are ascertained at low rates of 1% to 12% in primary care (PC). Underserved populations experience disparities of ascertainment, but data are lacking. INHERET is an online personal and family history tool to facilitate the identification of individuals who are eligible, according to guidelines, to be counseled on germline genetic testing and risk management. Patients and Methods: INHERET data entry uses cancer genetics clinic questionnaires and algorithms that process patient data through NCCN Clinical Practice Guidelines in Oncology and best practice guidelines. The tool was tested in silico on simulated and retrospective patients and prospectively in a pilot implementation trial. Patients in cancer genetics and in PC clinics were invited to participate via email or a card. Informed consent was completed online. Results: INHERET aimed to integrate patient data by algorithms based on professional and best practice guidelines to elicit succinct, actionable recommendations that providers can use without affecting clinic workflow or encounter length. INHERET requires a 4th-grade reading level, has simple navigation, and produces data lists and pedigree graphs. Prospective implementation testing revealed understandability of 90% to 100%, ease of use of 85%, and completion rates of 85% to 100%. Physicians using INHERET reported no added time to their encounters when patients were identified for counseling. In a specialty genetics clinic, INHERET’s data were input, on average, within 72 hours compared with 4 to 6 weeks through standard care, and the queue for scheduling patients decreased from 400 to fewer than 15 in <6 months. Conclusions: INHERET was found to be accessible for all education and age levels, except patients aged >70 years, who encountered more technical difficulties. INHERET aided providers in conveying high-risk status to patients and eliciting appropriate referrals, and, in a specialty clinic, it produced improved workflows and shortened queues.