Tech advances improve risk assessment and breast cancer management

By John Kontor, M.D., senior vice president, clinical technologies, Optum Insight

Importance of early diagnosis

Breast cancer remains the most frequently diagnosed cancer and second-leading cause of cancer deaths among women in the U.S. More than 40,000 women die from breast cancer each year.

Alarmingly, invasive breast cancers in younger women have increased significantly in recent years, leading the U.S. Preventive Services Task Force to recommend biannual screening for all women beginning at age 40 instead of 50, and continuing to age 74.

Early diagnosis and treatment are key to survival. When a tumor is detected early, the five-year relative survival rate is 99 percent. Unfortunately, more than a third of tumors are not diagnosed until they have spread beyond the breast. Black women and American Indian/Alaska Native women are most likely to be diagnosed in later stages, contributing to disproportionate mortality in these groups.

Lyda E. Rojas Carroll, M.D., chair of surgical specialties at Optum Medical Care, P.C. (Formerly CareMount) New York, recently shared with me the importance of early detection and understanding one's risks. "I encourage all my patients who are eligible to get a mammogram and spread the word about the importance of screening," she said. "By knowing their risk, patients can take proactive steps, such as lifestyle changes or preventive measures, to reduce that risk. we can provide personalized screening and treatment options and offer patients the best possible care."

We must do more to improve these outcomes. As we observe Breast Cancer Awareness Month, clinicians should be cognizant of ways technology is enhancing our ability to assess patients' risk of developing breast cancer, and to drive appropriate diagnostic testing and treatment earlier. New advances in AI-powered tools can help us reduce breast cancer morbidity and mortality.

Some technology considerations

Risk assessment - a crucial first step

Understanding an individual's risk of developing breast cancer is a crucial first step in ensuring early detection and assessing the need for regular mammograms or more aggressive screening. Many organizations across the US perform breast cancer risk assessments manually, a cumbersome, time-consuming and error-ridden method.

Technology enables automation of that process within the clinician workflow. Certain tools enable providers to initiate a personalized risk-score calculation during a patient's annual assessment or mammography screening using information and medical history from the patient's electronic health record (EHR). That patient's risk for developing breast cancer can then be calculated automatically using scoring models, such as the comprehensive Tyrer-Cuzick model, which takes into account personal and family risk factors such as breast density, use of hormone replacement therapy, and family history of breast cancer. After a score is calculated, the patient's results are stored in the EHR, and providers can initiate next steps based on each patient's risk score. These screening tools can be embedded in or integrated with the EHR.

Based on the risk assessment, providers can recommend the right modality for screening. For example, someone with a family history of cancer and dense breasts may need an ultrasound in addition to a mammogram.

This technology helps identify and prioritize vulnerable patients with higher risk to ensure they receive screening at the right time, so any tumors can be detected in the early stages.

Decision support tools provide evidence-based treatment recommendations

Along with risk assessment tools, clinicians can employ technology-based decision support tools to make better-informed decisions about which diagnostic tests and treatments are appropriate for individual patients.

Evidence-based clinical guidelines for use in diagnostics, imaging and oncology help to support appropriate utilization of the right test for the right patient. The guidelines do not replace a clinician's judgement, rather they provide evidence-based screening criteria that support evaluation of a patient's unique clinical information to determine an appropriate course of action. The guidelines are developed by expert clinicians who are trained in critical appraisal of medical literature, validated by extensive peer review, and are fully referenced and updated regularly.

When it comes to breast cancer, these guidelines can:

• Help determine appropriate tests for identifying molecular and genetic markers in individual patients, and the potential benefit to be gained from a specific therapy.
• Help determine the type of imaging test most appropriate for a patient based on their risk level, and limit patient exposure to unnecessary tests.
• Assess the medical appropriateness of surgical interventions, like mastectomy, and prompt consideration of less invasive treatment where applicable.
• Assist in the appropriate use of off-label prescription drugs and biologics.

Patients and their family members can feel confident that these tools provide the best available, objective interpretation of the evidence for different breast cancer tests and treatment they or their loved one may need to undergo.

Future state

Health technology companies are further refining existing tools and bringing new solutions to market to assist clinicians in early diagnosis and treatment. We're building models and gathering data to be able to pinpoint which patients need early engagement more proactively and then helping them engage.

Other solutions in imaging will assist radiologists in identifying small abnormalities in breast tissue that might be missed using current technology. With the rapid evolution of computer-aided detection and AI, smaller potentially malignant nodules and lesions can be highlighted sooner. Patients should discuss with their doctors the availability of AI for advanced review and consultation on their images.