Abstract P3-11-04: A model to predict high-risk Oncotype DX scores as defined by the TailorX trial: A report from the National Cancer Data Base
Authors: C Pesce, K Kuchta, E Wang, K Yao, M El-Tamer
Journal: Cancer Research (2019)

Abstract Background: Results from the TailorX clinical trial demonstrated a survival benefit of chemotherapy in those with high-risk (&amp;gt;25) Oncotype DX scores as well as in some patients ≤50yo with intermediate (16-25) scores. The objective of this study was to develop a model that could predict a high-risk Oncotype DX score based on tumor features alone. Methods: From 2010-2015, 84,549 breast cancer patients with Oncotype DX scores were selected from the National Cancer Data Base. Seven pathologic variables including age, estrogen and progesterone receptor status, histologic subtype, lymphovascular invasion (LVI), grade, and tumor size were used to predict high-risk (&amp;gt;25) Oncotype DX scores using logistic regression. A similar analysis was performed on women ≤50yo to predict low (&amp;lt;15) and intermediate (16-25) scores. Nomograms were created for models using bootstrap estimation method of the model coefficients. Cutoffs with at least 80% positive predictive value (PPV) were chosen to classify patients into high or low-risk Oncotype DX score groups. Accuracy of these predictions were developed in a training set and validated in a testing set. Results: For patients &amp;gt;50yo, 6,658 (15.1%) of patients had high-risk Oncotype DX scores. The model yielded a moderately strong C-index of 0.80 for Oncotype DX score of &amp;gt;25. For women ≤50yo, 2,044 (13.5%) were high-risk, 5,760 (38.1%) were intermediate-risk and 7,316 (48.4%) were low-risk. The C-index for women ≤50yo was 0.81 for prediction of Oncotype DX score of &amp;gt;25. C-indexes for intermediate and low risk scores were not strong enough to use for prediction (0.54 and 0.67). Estrogen receptor status, progesterone receptor status and grade were the strongest independent predictors of high-risk Oncotype DX scores in women &amp;gt;50yo and ≤50yo. Age was not a good predictor of high-risk scores in women &amp;gt;50yo. When our nomogram was used in the training set, the PPV of a high-risk Oncotype score was 80% with a negative predictive value (NPV) of 87%, sensitivity of 19% and specificity of 99%. In the testing set, PPV was 81%, with a NPV of 87%, sensitivity of 19% and specificity of 99%. Conclusion: A model incorporating tumor factors can predict a high-risk Oncotype DX score as defined by the recent TailorX trial in all age groups. The model is of limited value in predicting intermediate-risk Oncotype DX scores in women of age ≤50. In resource-constrained healthcare systems, such a model can help identify high risk patients who would benefit from adjuvant chemotherapy without incurring the cost of an Oncotype DX test. Citation Format: Pesce C, Kuchta K, Wang E, Yao K, El-Tamer M. A model to predict high-risk Oncotype DX scores as defined by the TailorX trial: A report from the National Cancer Data Base [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-11-04.