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Authors: Almstedt, Katrin
Mendoza, S.
Otto, M.
Battista, M. J.
Steetskamp, Joscha
Heimes, Anne-Sophie
Krajnak, Slavomir
Poplawski, A.
Gerhold-Ay, A.
Hasenburg, Annette
Denkert, Carsten
Schmidt, Marcus
Title: EndoPredict® in early hormone receptor-positive, HER2-negative breast cancer
Online publication date: 11-May-2021
Year of first publication: 2020
Language: english
Abstract: PURPOSE Evaluating consecutive early breast cancer patients, we analyzed both the impact of EndoPredict® on clinical decisions as well as clinico-pathological factors influencing the decision to perform this gene expression test. METHODS Hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer patients treated between 2011 and 2016 were included in this study to investigate the role of EndoPredict® (EPclin) in the treatment of early breast cancer. A main study aim was to analyze the changes in therapy recommendations with and without EPclin. In addition, the impact of clinico-pathological parameters for the decision to perform EPclin was examined by Pearson's chi-squared test (χ2-test) and Fisher's exact test as well as univariate and multivariate logistic regressions. RESULTS In a cohort of 869 consecutive early HR-positive, HER-negative breast cancer patients, EPclin was utilized in 156 (18.0%) patients. EPclin led to changes in therapy recommendations in 33.3% (n = 52), with both therapy escalation in 19.2% (n = 30) and de-escalation in 14.1% (n = 22). The clinico-pathological factors influencing the use of EPclin were age (P < 0.001, odds ratio [OR] 0.498), tumor size (P = 0.011, OR 0.071), nodal status (P = 0.021, OR 1.674), histological grade (P = 0.043, OR 0.432), and Ki-67 (P < 0.001, OR 3.599). CONCLUSIONS EPclin led to a change in therapy recommendations in one third of the patients. Clinico-pathological parameters such as younger age, smaller tumor size, positive nodal status, intermediate histological grade and intermediate Ki-67 had a significant influence on the use of EndoPredict®.
DDC: 610 Medizin
610 Medical sciences
Institution: Johannes Gutenberg-Universität Mainz
Department: FB 04 Medizin
Place: Mainz
Version: Published version
Publication type: Zeitschriftenaufsatz
License: CC BY
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Journal: Breast cancer research and treatment
Pages or article number: 137
Publisher: Springer Science + Business Media B.V.
Publisher place: Dordrecht
Issue date: 2020
ISSN: 1573-7217
Publisher URL:
Publisher DOI: 10.1007/s10549-020-05688-1
Appears in collections:JGU-Publikationen

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