Estimating the OncotypeDX score: Validation of an inexpensive estimation tool Journal Article
| Authors: | Eaton, A. A.; Pesce, C. E.; Murphy, J. O.; Stempel, M. M.; Patil, S. M.; Brogi, E.; Hudis, C. A.; El-Tamer, M. |
| Article Title: | Estimating the OncotypeDX score: Validation of an inexpensive estimation tool |
| Abstract: | 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%). © 2016, Springer Science+Business Media New York. |
| Keywords: | breast cancer; risk prediction; oncotypedx |
| Journal Title: | Breast Cancer Research and Treatment |
| Volume: | 161 |
| Issue: | 3 |
| ISSN: | 0167-6806 |
| Publisher: | Springer |
| Date Published: | 2017-02-01 |
| Start Page: | 435 |
| End Page: | 441 |
| Language: | English |
| DOI: | 10.1007/s10549-016-4069-4 |
| PROVIDER: | scopus |
| PUBMED: | 27928699 |
| PMCID: | PMC5310948 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 2 February 2017 -- Source: Scopus |
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