Autoren:	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
Titel:	EndoPredict® in early hormone receptor-positive, HER2-negative breast cancer
Online-Publikationsdatum:	11-Mai-2021
Erscheinungsdatum:	2020
Sprache des Dokuments:	Englisch
Zusammenfassung/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-Sachgruppe:	610 Medizin 610 Medical sciences
Veröffentlichende Institution:	Johannes Gutenberg-Universität Mainz
Organisationseinheit:	FB 04 Medizin
Veröffentlichungsort:	Mainz
ROR:	https://ror.org/023b0x485
DOI:	http://doi.org/10.25358/openscience-5804
Version:	Published version
Publikationstyp:	Zeitschriftenaufsatz
Nutzungsrechte:	CC BY
Informationen zu den Nutzungsrechten:	https://creativecommons.org/licenses/by/4.0/
Zeitschrift:	Breast cancer research and treatment 182
Seitenzahl oder Artikelnummer:	137 146
Verlag:	Springer Science + Business Media B.V.
Verlagsort:	Dordrecht
Erscheinungsdatum:	2020
ISSN:	1573-7217
URL der Originalveröffentlichung:	https://doi.org/10.1007/s10549-020-05688-1
DOI der Originalveröffentlichung:	10.1007/s10549-020-05688-1
Enthalten in den Sammlungen:	JGU-Publikationen