Abstract P1-06-12: Optimizing the use of oncotype Dx in early breast cancer

Abstract

Abstract Background: Oncotype Dx (ODX) prognosticates the risk of recurrence and predicts the benefit of adjuvant chemotherapy in estrogen-receptor-positive breast cancer (BC). However, its cost makes it prohibitive for many health care systems. Our objective was to develop a model that uses routine clinical and pathological parameters to identify ODX high risk patients which require adjuvant chemotherapy. Methods: We retrospectively reviewed ODX and pathology reports from 190 early BC patients treated between 2014 and 2016 in a specialized cancer center. Our population was divided into a training (n:133) and validation set (n:57). In the training set, among available clinico-pathological variables (age, T, ER, PR, Ki67, Elston-Ellis grade) a multiple linear regression model was carried out to select those significantly associated with ODX. Coefficients of statistically significant variables were used to build an equation. The equation was applied in the training set. These results were confronted to ODX categories. The best threshold for selecting high risk patients was identified in the training set and tested in the validation set. Results: Among the tested variables, tumor size (pT), progesterone receptor (PR), Ki67 and Ellston-Ellis grade were significantly associated with ODX RS (Table 1). The linear predictor is: (0.2544 x pT) – (0.0739 x PR) + (0.0861 x Ki67) + (5.4232 x Elston grade). The threshold score for this equation was set on 14 to discriminate high from low-intermediate risk patients. The test was able to correctly classify high risk patients with a sensitivity of 78%, a specificity of 72% and a negative predictive value of 98%. Conclusion: With further refinement ODX could be omitted in patients classified as high risk by our predictor therefore restricting and optimizing the use of ODX to a smaller population of patients. The observed ODX distribution in our patients is similar to previously reported series suggesting that this equation could be informative in similar clinical settings. Additional external testing using new datasets is ongoing. Citation Format: Ruiz R, Namuche F, Flores C, Aguilar A, Gomez HL. Optimizing the use of oncotype Dx in early breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-06-12.