Prognostic Comparison between Oncotype DX® and a 23-Gene Classifier, RecurIndex®, on the Taiwan Breast Cancer Population

Abstract

The applicability of the Oncotype DX® (Genomic Health, Inc., Redwood City, CA, USA) recurrence score (RS) in Asian populations is unclear. A 23-gene classifier, RecurIndex® (Amwise Diagnostics, Pte. Ltd., Singapore), has been developed based on the gene expression profiles of early-stage breast cancer patients of ethnic Han Chinese population in Taiwan. This study aimed to compare the performance of the Oncotype DX® RS with the RecurIndex® recurrence index (RI) for predicting relapse-free survival. Therefore, we calculated both the RI and RS for 110 early stage breast cancer patients, with the cut-off value for high-risk recurrence set at 26 and 29 for the RS and the RI, respectively. With relapse-free interval (RFI) as the primary endpoint, the concordance between RS and RI was 78.2% (Kappa value = 0.297). For a median follow-up interval of 27 months, there was a statistically significant difference in RFI between the high- and low-risk groups defined by the RI (p = 0.04) but not between risk groups defined by the RS (p = 0.66). In conclusion, whereas there was high concordance between the RecurIndex® RI and the Oncotype DX RS, the current data showed that the RI had a better discrimination for recurrence risk than the RS. Subsequent studies with larger sample sizes will be needed to confirm the superiority of the RI over the RS in the Asian population.

Select gene mutations associated with survival outcomes in ER‐positive ERBB2‐negative early‐stage invasive breast cancer: A single‐institutional tissue bank study

“…In the context of the current literature, the potential of multigene mutational panel testing for prognostic capability in patients with ER +/ERBB2‐ EBC remains largely unexplored. Previous studies have predominantly focused on examining the gene expression profiles to determine breast cancer prognosis 26–30 . Our research bridges this gap by applying widely available targeted sequencing to select cancer‐related genes and shows promise in identifying high‐risk patients who may benefit from more intensive surveillance or targeted interventions.…”

“…Previous studies have predominantly focused on examining the gene expression profiles to determine breast cancer prognosis. [26][27][28][29][30] Our research bridges this gap by applying widely available targeted sequencing to select cancer-related genes and shows promise in identifying high-risk patients who may benefit from more intensive surveillance or targeted interventions.…”