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Slembrouck L, Vanden Bempt I, Wildiers H, et al. Concordance between results of inexpensive statistical models and multigene signatures in patients with ER+/HER2- early breast cancer. Mod Pathol. 2021;34(7):1297-1309doi: 10.1038/s41379-021-00743-8.
Slembrouck, L., Vanden Bempt, I., Wildiers, H., Smeets, A., Van Rompuy, A. S., Van Ongeval, C., Jongen, L., Weltens, C., Punie, K., Hoste, G., Van Nieuwenhuysen, E., Han, S., Nevelsteen, I., Neven, P., & Floris, G. (2021). Concordance between results of inexpensive statistical models and multigene signatures in patients with ER+/HER2- early breast cancer. Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 34(7), 1297-1309. https://doi.org/10.1038/s41379-021-00743-8
Slembrouck, Laurence, et al. "Concordance between results of inexpensive statistical models and multigene signatures in patients with ER+/HER2- early breast cancer." Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc vol. 34,7 (2021): 1297-1309. doi: https://doi.org/10.1038/s41379-021-00743-8
Slembrouck L, Vanden Bempt I, Wildiers H, Smeets A, Van Rompuy AS, Van Ongeval C, Jongen L, Weltens C, Punie K, Hoste G, Van Nieuwenhuysen E, Han S, Nevelsteen I, Neven P, Floris G. Concordance between results of inexpensive statistical models and multigene signatures in patients with ER+/HER2- early breast cancer. Mod Pathol. 2021 Jul;34(7):1297-1309. doi: 10.1038/s41379-021-00743-8. Epub 2021 Feb 08. PMID: 33558657.
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Mod Pathol. 2021 Jul;34(7):1297-1309. doi: 10.1038/s41379-021-00743-8. Epub 2021 Feb 08.

Concordance between results of inexpensive statistical models and multigene signatures in patients with ER+/HER2- early breast cancer.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc

Laurence Slembrouck, Isabelle Vanden Bempt, Hans Wildiers, Ann Smeets, Anne-Sophie Van Rompuy, Chantal Van Ongeval, Lynn Jongen, Caroline Weltens, Kevin Punie, Griet Hoste, Els Van Nieuwenhuysen, Sileny Han, Ines Nevelsteen, Patrick Neven, Giuseppe Floris

Affiliations

  1. Department of Oncology, KU Leuven, Leuven, Belgium. [email protected].
  2. Deptartment of Human Genetics, University Hospitals Leuven, KU Leuven, Leuven, Belgium.
  3. Department of Oncology, KU Leuven, Leuven, Belgium.
  4. Department of General Medical Oncology, University Hospitals Leuven, Leuven, Belgium.
  5. Department of Surgical Oncology, University Hospitals Leuven, Leuven, Belgium.
  6. Department of Imaging and Pathology, KU Leuven, Leuven, Belgium.
  7. Department of Pathology, University Hospitals Leuven, Leuven, Belgium.
  8. Department of Radiology, University Hospitals Leuven, Leuven, Belgium.
  9. Department of Radiotherapy Oncology, University Hospitals Leuven, Leuven, Belgium.
  10. Department of Gynecology and Obstetrics, University Hospitals Leuven, Leuven, Belgium.

PMID: 33558657 DOI: 10.1038/s41379-021-00743-8

Abstract

Multigene signatures (MGS) are used to guide adjuvant chemotherapy (aCT) decisions in patients diagnosed with estrogen receptor (ER)-positive HER2-negative early breast cancer. We used results from three MGS (Oncotype DX® (ODX), MammaPrint® (MP) or Prosigna®) and assessed the concordance between high or low risk of recurrence and the predicted risk of recurrence based on statistical models. In addition, we looked at the impact of MGS results on final aCT administration during the multidisciplinary meeting (MDM). We retrospectively included 129 patients with ER-positive HER2-negative early breast cancer for which MGS testing was performed after MDM at University Hospitals Leuven between May 2013 and April 2019 in case there was doubt about aCT recommendation. Tumor tissue was analyzed either by ODX (N = 44), MP (N = 28), or Prosigna® (N = 57). Eight statistical models were computed: Magee equations (ME), Memorial Sloan Kettering simplified risk score (MSK-SRS), Breast Cancer Recurrence Score Estimator (BCRSE), OncotypeDXCalculator (ODXC), new Adjuvant! Online (nAOL), Mymammaprint.com (MyMP), PREDICT, and SiNK. Concordance, negative percent agreement, and positive percent agreement were calculated. Of 129 cases, 53% were MGS low and 47% MGS high risk. Concordances of 100.0% were observed between risk results obtained by ODX and ME. For MP, BCRSE demonstrated the best concordance, and for Prosigna® the average of ME. Concordances of <50.0% were observed between risk results obtained by ODX and nAOL, ODX and MyMP, ODX and SiNK, MP and MSK-SRS, MP and nAOL, MP and MyMP, MP and SiNK, and Prosigna® and ODXC. Integration of MGS results during MDM resulted in change of aCT recommendation in 47% of patients and a 15% relative and 9% absolute reduction. In conclusion, statistical models, especially ME and BCRSE, can be useful in selecting ER-positive HER2-negative early breast cancer patients who may need MGS testing resulting in enhanced cost-effectiveness and reduced delay in therapeutic decision-making.

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