Risk stratification in early-stage estrogen receptor+/HER2-breast cancer patients: Comparative analysis of cost-effective methods

Abstract

Context: Treatment decisions in early-stage hormone receptor-positive breast cancer patients are dependent on the potential risk of cancer recurrence. Multiple expensive gene expression based or cost-effective methods are used to assess the risk in conjunction with traditional prognostic determinants – age, tumor parameters – size, node, grade, and gold standard biomarkers-estrogen receptor, progesterone receptor (PR), and Human epidermal growth factor receptor 2. Aim: The aim of this study is to compare the performance of multiple economic methods, namely, (1) Ki67; (2) immunohistochemistry 4 (IHC4)-multi-biomarker test; (3) Luminal A/B subtyping (4) PREDICT-an online tool. Settings and Design: IHC was performed as per standard protocol on a retrospective cohort of 401 patients. The Kaplan–Meier analysis and Cox proportional-hazards model were used. Results: The results confirmed that lymph node status is the most useful prognostic indicator among the traditional clinicopathological parameters. IHC4 had a hazard ratio (HR) of 2.847 and separated the low-, intermediate- and high-risk groups significantly (P = 0.0248). Luminal subtyping (HR = 2.530) also stratified the two risk groups significantly (P = 0.0321), but had HR lesser than IHC4. Ki67 and PREDICT could not separate the cohort into low- and high-risk groups with statistical significance. All tools compared separated the low-, intermediate- and high-risk groups with a maximum of 7% difference in metastasis-free survival significantly less compared to Oncotype Dx, which separates with 28% difference in survival. Conclusions: IHC4 is a significant predictor of prognosis among the four tools tested. However, multiple limitations of IHC4 tool about validation and lack of standardized protocols for IHC create a need for a robust, accurate, and cost-effective risk assessment tool.