Estimating the OncotypeDX score: validation of an inexpensive estimation tool.

BACKGROUND

OncotypeDX, a multi-gene expression assay, has been incorporated into clinical practice as a prognostic and predictive tool. However, its use in resource-constrained international healthcare systems is limited. Here we develop and validate a simplified model using clinicopathologic criteria to predict OncotypeDX score.

METHODS

Patients with estrogen receptor (ER) and/or progesterone receptor (PR)-positive and HER2-negative invasive ductal carcinoma for whom the OncotypeDX test was successfully performed between 09/2008 and 12/2011 were retrospectively identified. Tumor size, nuclear and histologic grade, lymphovascular invasion, and ER and PR status were extracted from pathology reports. Data were split into a training dataset comprising women tested 09/2008-04/2011, and a validation dataset comprising women tested 04/2011-12/2011. Using the training dataset, linear regression analysis was used to identify factors associated with OncotypeDX score, and to create a simplified risk score and identify risk cutoffs.

RESULTS

Estrogen and progesterone receptors, tumor size, nuclear and histologic grades, and lymphovascular involvement were independently associated with OncotypeDX. The full model explained 39% of the variation in the test data, and the simplified risk score and cutoffs assigned 57% of patients in the test data to the correct risk category (OncotypeDX score <18, 18-30, >30). 41% of patients were predicted to have OncotypeDX score <18, of these 83, 16, and 2% had true scores of <18, 18-30, and >30, respectively.

CONCLUSIONS

Awaiting an inexpensive test that is prognostic and predictive, our simplified tool allows clinicians to identify a fairly large group of patients (41%) with very low chance of having high-risk disease (2%).