Dr. Graff on Genomic Risk Prediction in HR+/HER2- Breast Cancer | OncLive

Dr. Graff on Genomic Risk Prediction in HR+/HER2- Breast Cancer

April 11, 2020

Stephanie L. Graff, MD, discusses genomic risk prediction in patients with hormone receptor–positive, HER2-negative breast cancer.

Stephanie L. Graff, MD, director of the Breast Program at the Sarah Cannon Cancer Institute of HCA Midwest Health and associate director of the Breast Cancer Research Program at Sarah Cannon Research Institute, discusses genomic risk prediction in patients with hormone receptor (HR)—positive, HER2-negative breast cancer.

The phase III TAILORx study enrolled women with HR-positive, HER2—negative, axillary node–negative breast cancer. Approximately 69% of patients had a midrange recurrence score of 11 to 25 and were randomly assigned to receive either chemoendocrine therapy or endocrine therapy alone. Endocrine therapy proved to be noninferior to chemoendocrine therapy in terms of invasive disease-free survival.

This study showed that genomic risk prediction is a stronger tool to utilize than clinical risk, says Graff. Genomic score outperforms tumor size and grade, adds Graff. The role of the clinical predictors is personalizing care for women with intermediate Oncotype recurrence scores between 14 and 20; this is where the benefit of chemotherapy starts to be incrementally larger based on patients’ overall clinical risk profile, concludes Graff.


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