Developing a clinical-pathologic model to predict genomic risk of recurrence in patients with hormone receptor positive, human epidermal growth factor receptor-2 negative, node negative breast cancer

Abstract

Introduction: Patients with hormone receptor (HR)-positive, human epidermal growth factor receptor-2 (HER2)-negative, node negative (NN) breast cancer may be offered a gene expression profiling (GEP) test to determine recurrence risk and benefit of adjuvant chemotherapy. We developed a clinical-pathologic (CP) model to predict genomic recurrence risk and examined its performance characteristics. Methods: Patients diagnosed with HR-positive, HER2-negative, NN breast cancer with a tumour size 20 mm (odds ratio [OR], 3.58; 95% confidence interval [CI], 1.84–6.98; P<0.001), low expression of progesterone receptor (OR, 3.46; 95% CI, 1.76–6.82; P<0.001), and histological grade III (OR, 7.24; 95% CI, 3.82–13.70; P<0.001) predicted high genomic risk. A CP model using these variables was developed to provide a score of 0–4. A CP cut-point of 0, identified 56% of genomic low risk patients with a specificity of 98.4%. Conclusions: A CP model could be used to narrow the population of breast cancer patients undergoing GEP testing.

Keywords

• Node negative breast cancer
• Gene expression profiling
• Clinical-pathologic model
• OncotypeDX
• Prosigna