Prediction of Oncotype DX Recurrence Score Based on Systematic Evaluation of Ki-67 Scores in Hormone Receptor-Positive Early Breast Cancer.

Abstract

Purpose: Oncotype DX (ODX) predicts the risk of recurrence and benefits of adding chemotherapy for patients with estrogen receptor positive (ER+)/human epidermal growth factor receptor 2 negative (HER2-) early-stage breast cancer. We aimed to develop a simplified scoring system using readily available clinicopathological parameters to predict a high-risk ODX recurrence score (RS) while minimizing reproducibility issues regarding Ki-67 index evaluation methods.

Methods: We enrolled 300 patients with ER+/HER2- early breast cancer, for whom ODX RS data were available in the test set. Using the QuPath image analysis platform, we systematically evaluated the average, hotspot, and hottest spot Ki-67 scores in the test set. Logistic regression analyses were conducted to establish a predictive scoring system for high-risk ODX RS. An independent validation set comprising 117 patients over different periods was established.

Results: Factors such as age ≤ 50 years, invasive ductal carcinoma tumor type, histologic grade 2 or 3, tumor necrosis, progesterone receptor negativity, and a high Roche-analyzed Ki-67 score (> 20) were associated with high-risk ODX RS. These variables were incorporated into our scoring system. The area under the curve of the scoring system was 0.8057. When applied to both the test and validation sets with a cutoff value of 3, the sensitivity of our scoring system was 92%.

Conclusion: We successfully developed a scoring system based on the systematic evaluation of Ki-67 scoring methods. We believe that our user-friendly predictive scoring system for high risk ODX RS could help clinicians in identifying patients who may or may require additional ODX testing.