The MAGIC survey in hormone receptor positive (HR+), HER2-negative (HER2−) breast cancer: When might multigene assays be of value?

Abstract

BackgroundA modest proportion of patients with early stage hormone receptor-positive (HR+), HER2-negative (HER2−) breast cancer benefit from adjuvant chemotherapy. Traditionally, treatment recommendations are based on clinical/pathologic criteria that are not predictive of chemotherapy benefit. Multigene assays provide prognostic and predictive information that can help to make more informed treatment decisions. The MAGIC survey evaluated international differences in treatment recommendations, how traditional parameters are used for making treatment choices, and for which patients treating physicians feel most uncertain about their decisions. MethodsThe MAGIC survey captured respondents' demographics, practice patterns, relevance of traditional parameters for treatment decisions, and use of or interest in using multigene assays. Using this information, a predictive model was created to simulate treatment recommendations for 672 patient profiles. ResultsThe survey was completed by 911 respondents (879 clinicians, 32 pathologists) from 52 countries. Chemo-endocrine therapy was recommended more often than endocrine therapy alone, but there was substantial heterogeneity in treatment recommendations in 52% of the patient profiles; approximately every fourth physician provided a different treatment recommendation. The majority of physicians indicated they wanted to use multigene assays clinically. Lack of reimbursement/availability were the main reasons for non-usage. ConclusionsThe survey reveals substantial heterogeneity in treatment recommendations. Physicians have uncertainty in treatment recommendations in a high proportion of patients with intermediate risk features using traditional parameters. In HR+, HER2− patients with early disease the findings highlight the need for additional markers that are both prognostic and predictive of chemotherapy benefit that may support more-informed treatment decisions.