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

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 (χ 2-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 ® .

Comparison of risk assessment in 1652 early ER positive, HER2 negative breast cancer in a real-world data set: classical pathological parameters vs. 12-gene molecular assay (EndoPredict)

“…They also showed noteworthy discordances for low grade tumors and high EP test results and vice versa. The proportion of EPclin high risk tumors in the Ki67 low (≤ 20%) group is nearly 47% being close to our results (42.2%) [21].…”

Survival analysis across the entire transcriptome identifies biomarkers with the highest prognostic power in breast cancer

“…The basic systemic therapy for these patients includes chemotherapy and endocrine therapy – we evaluated biomarkers of endocrine therapy previously [23] . The decision to administer chemotherapy can be based on clinical features including high stage or node positivity, or designation of high risk via gene expression profiles including Oncotype DX [24] , [25] or EndoPredict [26] . Here, we run survival analysis for all genes in all chemotherapy treated ER positive ERBB2 negative patients to uncover genes correlated to survival following chemotherapy.…”

Luminal Breast Cancer: Risk of Recurrence and Tumor-Associated Immune Suppression

“…So far, a variety of gene-expression-profiling methods, such as Oncotype DX [36], MammaPrint [37], PAM50 [38], Breast Cancer Index [39], PREDICT score [40,41], IHC4score [42,43], Clinical Treatment Score (CTS) [44], Magee equation [45], and EndoPredict [46] have been developed to increase the accuracy on the prediction of the risk of recurrence, in order to guide treatment decisions (mainly adjuvant CT vs. no) in luminal subtypes. Unfortunately, none of these tests are currently used in clinical practice.…”