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Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset.

Publication ,  Journal Article
Harowicz, MR; Robinson, TJ; Dinan, MA; Saha, A; Marks, JR; Marcom, PK; Mazurowski, MA
Published in: Breast Cancer Res Treat
February 2017

PURPOSE: Given the potential savings in cost and resource utilization, several algorithms have been proposed to predict Oncotype DX recurrence score (ODX RS) using commonly acquired histopathologic variables. Although it is promising, additional independent validation of these surrogate markers is needed prior to guide the patient management. METHODS: In this retrospective study, we analyzed 305 patients with invasive breast cancer at our institution who had ODX RS available. We selected five equations that provide a surrogate measure of ODX as previously published by Klein et al. (Magee equations 1-3), Gage et al., and Tang et al. All equations used estrogen receptor status and progesterone receptor status along with different combinations of grade, proliferation indices (Ki-67, mitotic rate), HER2 status, and tumor size. RESULTS: Of all surrogate scores tested, the Magee equation 2 provided the highest correlation with ODX both with regard to raw score (Pearson's correlation coefficient = 0.66 95% CI 0.59-0.72) and categorical correlation (Cohen's kappa = 0.43, 95% CI 0.33-0.53). Although Magee equation 2 provided a way to reliably identify high-risk disease by assigning 95% of the patients with high ODX RS to either the intermediate- or high-risk group, it was unable to reliably identify the potential for patients to have intermediate- or high-risk disease by ODX (66% of such patients identified). CONCLUSIONS: Although commonly available surrogates for ODX appear to predict high-risk ODX RS, they are unable to reliably rule out the presence of patients with intermediate-risk disease by ODX. Given the potential benefit of adjuvant chemotherapy in women with intermediate-risk disease by ODX, current surrogates are unable to safely substitute for ODX. Characterizing the true recurrence risk in patients with intermediate-risk disease by ODX is critical to the clinical adoption of current surrogate markers and is an area of ongoing clinical trials.

Duke Scholars

Published In

Breast Cancer Res Treat

DOI

EISSN

1573-7217

Publication Date

February 2017

Volume

162

Issue

1

Start / End Page

1 / 10

Location

Netherlands

Related Subject Headings

  • Risk Factors
  • Retrospective Studies
  • Prognosis
  • Oncology & Carcinogenesis
  • Neoplasm Staging
  • Neoplasm Recurrence, Local
  • Neoplasm Grading
  • Middle Aged
  • Humans
  • Genetic Testing
 

Citation

APA
Chicago
ICMJE
MLA
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Harowicz, M. R., Robinson, T. J., Dinan, M. A., Saha, A., Marks, J. R., Marcom, P. K., & Mazurowski, M. A. (2017). Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset. Breast Cancer Res Treat, 162(1), 1–10. https://doi.org/10.1007/s10549-016-4093-4
Harowicz, Michael R., Timothy J. Robinson, Michaela A. Dinan, Ashirbani Saha, Jeffrey R. Marks, P Kelly Marcom, and Maciej A. Mazurowski. “Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset.Breast Cancer Res Treat 162, no. 1 (February 2017): 1–10. https://doi.org/10.1007/s10549-016-4093-4.
Harowicz MR, Robinson TJ, Dinan MA, Saha A, Marks JR, Marcom PK, et al. Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset. Breast Cancer Res Treat. 2017 Feb;162(1):1–10.
Harowicz, Michael R., et al. “Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset.Breast Cancer Res Treat, vol. 162, no. 1, Feb. 2017, pp. 1–10. Pubmed, doi:10.1007/s10549-016-4093-4.
Harowicz MR, Robinson TJ, Dinan MA, Saha A, Marks JR, Marcom PK, Mazurowski MA. Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset. Breast Cancer Res Treat. 2017 Feb;162(1):1–10.
Journal cover image

Published In

Breast Cancer Res Treat

DOI

EISSN

1573-7217

Publication Date

February 2017

Volume

162

Issue

1

Start / End Page

1 / 10

Location

Netherlands

Related Subject Headings

  • Risk Factors
  • Retrospective Studies
  • Prognosis
  • Oncology & Carcinogenesis
  • Neoplasm Staging
  • Neoplasm Recurrence, Local
  • Neoplasm Grading
  • Middle Aged
  • Humans
  • Genetic Testing