A Validated Model for Identifying Patients Unlikely to Benefit From the 21-Gene Recurrence Score Assay

Predicting recurrence risk and chemotherapy benefit in early-stage breast cancer is challenging. The Oncotype DX gene assay is often used. Using a database of 221 patients a simple 2-rule model was developed and validated on an independent group of 319 patients. The model categorizes patients unlikely to benefit from the test thus achieving significant avoidance of cost. Background: Predicting recurrence risk and chemotherapy benefit in early-stage breast cancer can be challenging, and Oncotype DX (ODX) is often used to gain insight. However, it is still unclear whether ODX can benefit in all cases. To clarify ODX's usefulness we sought to develop a model using readily available pathologic markers to help clinicians make that determination. Patients and Methods: Clinical pathologic data from 221 hormone receptor-positive, HER2-negative invasive breast cancer patients was used to create a model. The model was then validated on a second institution's set of 319 patients. Results: The model has 2 simple rules: low grade and positive progesterone receptor tumors (LG+PR) are low risk, and high grade or low estrogen receptor (ER) (ER < 20%) tumors (HG/LER) are high risk. The TAILORx (Trial Assigning Individualized Options for Treatment (Rx)) trial thresholds of Recurrence Score (RS) <= 10, when chemotherapy is of little benefit, and RS >= 26 when chemotherapy might be beneficial were used to judge model performance. Impressively, the misclassifications of an HG/LER patient who has an RS <= 10 were 0% and 2%, and for LG+PR patients who had an RS >= 26 were 0% and 2.6%. In the validation set, 28% (66 of 232) of the indeterminate group (neither in the HG/LER nor the LG+PR groups) had an RS <= 10 or an RS >= 26; this group might clinically benefit from ODX. Conclusion: A simple 2-rule model based on readily available pathologic data was developed and validated, which categorized patients into high and low risk for recurrence. Identification of patients who are unlikely to benefit from ODX testing could result in significant cost avoidance.