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. 2020 Jul;182(1):137-146.
doi: 10.1007/s10549-020-05688-1. Epub 2020 May 20.

EndoPredict® in early hormone receptor-positive, HER2-negative breast cancer

K Almstedt  1 , S Mendoza  2 , M Otto  3 , M J Battista  2 , J Steetskamp  2 , A S Heimes  2 , S Krajnak  2 , A Poplawski  4 , A Gerhold-Ay  4 , A Hasenburg  2 , C Denkert  5 , M Schmidt  2
Affiliations

EndoPredict® in early hormone receptor-positive, HER2-negative breast cancer

K Almstedt et al. Breast Cancer Res Treat. 2020 Jul.

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®.

Keywords: Early breast cancer; EndoPredict®; Endocrine therapy; Gene expression; Prognosis; Treatment decision.

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Conflict of interest statement

K. Almstedt received speaker honoraria from Roche Pharma AG, Pfizer Pharma GmbH and AstraZeneca. M. Schmidt received honoraria for speaker or consultancy role from AMGEN, AstraZeneca, Eisai, Lilly, Myelo Therapeutics, Novartis, Pantarhei Bioscience, Pfizer, and Roche. He received research funding from AstraZeneca, BioNTech, Eisai, Genentech, Myelo Therapeutics, Novartis, Pantarhei Bioscience, Pfizer, Pierre Fabre, and Roche. He received travel reimbursement from Pfizer and Roche. M. Otto received honoraria for speaker or consultancy role from AstraZeneca, Boehringer-Ingelheim, Roche and Sividon. He received travel reimbursement from AstraZeneca, and Boehringer-Ingelheim. MJ. Battista received honoraria for speaker or consultancy role from AstraZenca, MSD, PharmaMar, Roche Pharma AG, TEVA, Tesaro. He received travel reimbursement from Celgene, PharmaMar and Pierre Fabre. S. Krajnak received speaker honoraria from Roche. He received research funding from Novartis. He received travel reimbursement from PharmaMar. A. Hasenburg received honoraria from AstraZeneca, Celegen, MedConcept Gm, Med update GmbH, Medicultus, Pfizer, Promedicis GmbH, Pierre Fabre, Softconsult, Roche Pharma AG, Streamedup!GmbH and Tesaro Bio Germany GmbH. She is a member of the advisory board of PharmaMar, Promedicis GmbH, Pierre Fabre Pharma GmbH, Roche Pharma AG and Tesaro Bio Germany GmbH. She received research funding from Celgene. C. Denkert has been cofounder and shareholder of Sividon Diagnostics (now Myriad), has received speaker honoraria from Teva, Novartis, Pfizer, Roche, Amgen and has been consultant for MSD Oncology, Amgen, Roche and Daiichi-Sankyo. All other authors declare that they have no conflicts of interest.

Figures

Fig. 1
Fig. 1
Patient enrollment
Fig. 2
Fig. 2
EndoPredict® determination and allocation
Fig. 3
Fig. 3
Changes in therapy decision
See this image and copyright information in PMC

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