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EndoPredict improves the prognostic classification derived from common clinical guidelines in ER-positive, HER2-negative early breast cancer
Open accessAbstract
BACKGROUND: In early estrogen receptor (ER)-positive/HER2-negative breast cancer, the decision to administer chemotherapy is largely based on prognostic criteria. The combined molecular/clinical EndoPredict test (EPclin) has been validated to accurately assess prognosis in this population. In this study, the clinical relevance of EPclin in relation to well-established clinical guidelines is assessed. PATIENTS AND METHODS: We assigned risk groups to 1702 ER-positive/HER2-negative postmenopausal women from two large phase III trials treated only with endocrine therapy. Prognosis was assigned according to National Comprehensive Cancer Center Network-, German S3-, St Gallen guidelines and the EPclin. Prognostic groups were compared using the Kaplan-Meier survival analysis. RESULTS: After 10 years, absolute risk reductions (ARR) between the high- and low-risk groups ranged from 6.9% to 11.2% if assigned according to guidelines. It was at 18.7% for EPclin. EPclin reassigned 58%-61% of women classified as high-/intermediate-risk (according to clinical guidelines) to low risk. Women reclassified to low risk showed a 5% rate of distant metastasis at 10 years. CONCLUSION: The EPclin score is able to predict favorable prognosis in a majority of patients that clinical guidelines would assign to intermediate or high risk. EPclin may reduce the indications for chemotherapy in ER-positive postmenopausal women with a limited number of clinical risk factors.
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Cited by
Duffy, M. J., Harbeck, N., Nap, M., Molina, R., Nicolini, A., Senkus, E., & Cardoso, F. (2017) · European Journal of Cancer · doi:10.1016/j.ejca.2017.01.017 · Cited by 522
Luminal breast cancer: from biology to treatment
Ignatiadis, M., & Sotiriou, C. (2013) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2013.124 · Cited by 469
Improved breast cancer histological grading using deep learning
Wang, Y., Acs, B., Robertson, S., Liu, B., Solorzano, L., Wählby, C., Hartman, J., & Rantalainen, M. (2022) · Annals of Oncology · doi:10.1016/j.annonc.2021.09.007 · Cited by 211
Metadata
- Authors
- Dubsky, P., Filipits, M., Jakesz, R., Rudas, M., Singer, C. F., Greil, R., Dietze, O., Luisser, I., Klug, E., Sedivy, R., Bachner, M., Mayr, D., Schmidt, M., Gehrmann, M. C., Petry, C., Weber, K. E., Kronenwett, R., Brase, J. C., & Gnant, M.
- Venue
- Annals of Oncology
- Publisher
- Elsevier BV
- Published
- 2013-03
- Volume
- 24
- Issue
- 3
- Pages
- 640-647
- ISSN
- 0923-7534 (ISSN-L)
- OpenAlex
- W2144335178
- Cited by
- 212
- References
- 0
- FWCI
- 5.37
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- The paper
- Dubsky, P., Filipits, M., Jakesz, R., Rudas, M., Singer, C. F., Greil, R., Dietze, O., Luisser, I., Klug, E., Sedivy, R., Bachner, M., Mayr, D., Schmidt, M., Gehrmann, M. C., Petry, C., Weber, K. E., Kronenwett, R., Brase, J. C., & Gnant, M. (2013). EndoPredict improves the prognostic classification derived from common clinical guidelines in ER-positive, HER2-negative early breast cancer. Annals of Oncology. https://doi.org/10.1093/annonc/mds334
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