A simplified risk scoring system for predicting high-risk groups in gene expression tests for patients with estrogen receptor-positive, human epidermal growth factor receptor 2-negative, and node-positive breast cancer

Abstract

Purpose

The gene expression test (GET) was used to predict the response to chemotherapy and the recurrence risk. Several randomized clinical trials have demonstrated that some patients with node-positive disease can achieve favorable survival outcomes even without adjuvant chemotherapy. This study aimed to predict the results of Oncotype DX (Genomic Health) and MammaPrint (Agendia) using traditional clinicopathological factors.

Methods

We reviewed the records of 311 patients who underwent GET for hormone receptor-positive/human epidermal growth factor receptor 2 (HER2)-negative primary invasive breast cancer with node-positive disease between 2015 and 2022 at Severance Hospital and Gangneung Asan Medical Center. Univariate and multivariate logistic regression analyses assessed the relationships between clinicopathological variables and risk stratification using the GET results.

Results

A simple scoring system was created by assigning integer values to each variable. A score of 3 was assigned for histological grade 3, a score of 2 for pathologic T2 or above, and a score of 1 for a lower progesterone receptor (1–20 or Alled score 3–6), HER2 2-positive, and high Ki-67 (>20). In the validation cohort, overall accuracy was 0.798 (95% confidence interval, 0.744–0.844).

Conclusion

The high GET risk results can be predicted using traditional clinicopathological factors: tumor size, progesterone receptor, histological grade, HER2, and Ki-67. These results will be useful for treatment decision-making among clinically high-risk patients with HR-positive/HER2-negative and node-positive disease, helping to identify patients to whom the GET assay may not apply.