A validated model for identifying patients unlikely to benefit from the 21-gene recurrence score assay

Michele M. Gage, Martin Rosman, W. Charles Mylander, Erica Giblin, Hyun Seok Kim, Leslie Cope, Christopher Umbricht, Antonio C. Wolff, Lorraine Tafra

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)467-472
Number of pages6
JournalClinical Breast Cancer
Issue number6
StatePublished - Dec 2015


  • Classification model
  • Grade
  • Oncotype DX
  • Predictive value of tests
  • Risk assessment
  • Tumor markers

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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