Utilization of the 21-Gene Recurrence Score in a Diverse Breast Cancer Patient Population: Development of a Clinicopathologic Model to Predict High-Risk Scores and Response to Neoadjuvant Chemotherapy
Park KU, Chen Y, Chitale D, Choi S, Ali H, Nathanson SD, Bensenhaver J, Proctor E, Petersen L, Loutfi R, Simonds A, Kuklinski M, Doyle T, Dabak V, Cole K, Davis M, Newman L. Utilization of the 21-Gene Recurrence Score in a Diverse Breast Cancer Patient Population: Development of a Clinicopathologic Model to Predict High-Risk Scores and Response to Neoadjuvant Chemotherapy. Ann Surg Oncol. 2018 Jul;25(7):1921-1927.
Annals of surgical oncology : the official journal of the Society of Surgical Oncology
INTRODUCTION: The 21-gene expression profile [Oncotype DX Recurrence Score (RS)] stratifies benefit from adjuvant chemotherapy in hormone receptor (HR)-positive, HER2/neu-negative, node-negative breast cancer. It is not routinely applied to predict neoadjuvant chemotherapy (NACT) response; data in diverse patient populations also are limited. We developed a statistical model based on standard clinicopathologic features to identify high-risk cases (RS > 30) and then evaluated ability of predicted high RS to predict for NACT downstaging.
METHODS: Primary surgery patients with Oncotype DX RS testing 2012-2016 were identified from a prospectively-maintained database. A RS predictive model was created and applied to a dataset of comparable NACT patients. Response was defined as tumor size decrease ≥ 1 cm.
RESULTS: Of 394 primary surgery patients-60.4% white American; 31.0% African American-RS distribution was similar for both groups. No single feature reliably identified high RS patients; however, a model accounting for age, HR expression, proliferative index (MIB1/Ki67), histology, and tumor size was generated, with receiver operator area under the curve 0.909. Fifty-six NACT patients were identified (25 African American). Of 21 cases with all relevant clinicopathology, 14 responded to NACT and the model generated high-risk RS in 14 (100%); conversely, of 16 cases generating high-risk RS, only 2 did not respond.
CONCLUSIONS: Predictive modelling can identify high RS patients; this model also can identify patients likely to experience primary tumor downstaging with NACT. Until this model is validated in other datasets, we recommend that Oncotype-eligible patients undergo primary surgery with decisions regarding chemotherapy made in the adjuvant setting.
Medical Subject Headings
Antineoplastic Combined Chemotherapy Protocols; Biomarkers, Tumor; Breast Neoplasms; Carcinoma, Ductal, Breast; Carcinoma, Lobular; Female; Follow-Up Studies; Gene Expression Profiling; Humans; Middle Aged; Neoadjuvant Therapy; Neoplasm Invasiveness; Neoplasm Recurrence, Local; Prognosis; Survival Rate