Abstract 4268: Magee Equations for predicting Oncotype DX recurrence risk: A further evaluation using a large independent data set
Authors: Dooman Arefan, Rohit Bhargava, David Dabbs, Rachel C. Jankowitz, Shandong Wu
Journal: Cancer Research (2018)

Abstract Purpose: Oncotype DX 21-gene assay is a costly clinical method to predict the risk of breast cancer recurrence in lymph node-negative and estrogen receptor (ER)-positive breast cancers. Magee Equations were linear regression models developed working on several standard clinically available histopathological markers for predicting the Oncotype DX risk score, with the intention to save expenses and time. Magee Equations were derived from 817 patients and initially evaluated on 255 separate patients, now publically accessible online to compute estimations of recurrence risk scores. The purpose of this study was to conduct a further validation of Magee Equations using a much larger independent dataset to examine its robustness in comparison to the initial evaluation. Methods and Materials: In a HIPAA-compliant and IRB-approved study, we collected 1,391 patients with invasive breast cancer at our institution and all those patients have Oncotype DX risk score available. This cohort is independent of all previous patient populations associated with the development and initial evaluation of Magee Equations. Out of the 1,391 patients, 1,210 have available the related histopathologic markers that had been used in Magee Equations, including ER status, progesterone receptor (PR) status, human epidermal growth factor receptor 2 (HER2) status, proliferation indices (Ki-67), Nottingham grade, and tumor size. We ran the three different forms of Magee Equations on all the 1,210 patients and compared the estimation output of each equation to the truth, i.e., the actual Oncotype DX risk score. The estimation results on the 1,210 patients were evaluated by two metrics: concordance and Pearson's correlation coefficients, and compared to the reported initial evaluation performance of Magee Equations on the 255 patients. Results: On the 1,210 cases, the concordance on the recurrence risk categories (i.e., low, intermediate, and high) between the actual Oncotype DX categories and the three Magee Equation-predicted categories was 61.9% (Eq. 1), 59.8% (Eq. 2), and 63.4% (Eq. 3), respectively, corresponding to the initial evaluation performance of 55.8%, 59.4%, and 54.4%. After eliminating the intermediate category, the concordance of the three equations increased to 99.0%, 98.3%, and 99.1%, respectively, corresponding to the initial performance of 100%, 98.6%, and 98.7%. Likewise, the Pearson's correlation on the continuous risk scores was 53.7%, 54.4%, and 56.2% for equations 1, 2, and 3, respectively, corresponding to the initial Pearson's correlation of 61.6%, 60.3%, and 59.4%. Conclusions: Magee Equations remain stable on 1,210 independent new patients, comparable to the initially reported evaluation performance. Clinical outcome studies are required to test the usefulness of Magee Equations as a stand-alone test. Citation Format: Dooman Arefan, Rohit Bhargava, David Dabbs, Rachel C. Jankowitz, Shandong Wu. Magee Equations for predicting Oncotype DX recurrence risk: A further evaluation using a large independent data set [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4268.