Hormone Receptor-Positive / HER2-Negative Early Breast Cancer High-Risk Population: An Algorithm for Optimization Systemic Adjuvant Treatment Based on 2022 Updates.
Daniel González-HurtadoSergio RiveroJuan Carlos Samamé Pérez-VargasFernando E PetracciPublished in: Breast cancer : basic and clinical research (2023)
Prognostic and predictive factors for early and late distant distance recurrence risk in estrogen-receptor positive and HER2-receptor negative early breast cancer are well known, but not all these variables work equally for the prediction. The following are the most widely accepted variables for categorizing risk levels: clinic-pathologic features (tumor size, lymph node involvement, histological grade, age, menopausal status, Ki-67 expression, estrogen, and progesterone expression), primary systemic treatment response (pathologic response and/or Ki-67 downstaging), and gene expression signatures stratification. Treatment guidelines from cancer societies and collaborative groups, online predict-tools, real-world data and experts' opinion recommends different adjuvant strategies (chemotherapy, endocrine therapy, ovarian suppression, olaparib, or abemaciclib) depending on the low (< 10%), intermediate (10%-20%) or high-risk of distance recurrence at least in the first 5 years. Multiple randomized prospective trials were updated in 2022, that evidence allow us to perform a stratification of risk in pre- and postmenopausal women with estrogen-receptor positive and HER2-receptor negative early breast cancer based on a combination of clinic-pathologic features and genomic assays and guide the adjuvant systemic treatment recommendation for those with high risk.
Keyphrases
- estrogen receptor
- early breast cancer
- neoadjuvant chemotherapy
- lymph node
- gene expression
- locally advanced
- dna methylation
- primary care
- stem cells
- binding protein
- randomized controlled trial
- deep learning
- genome wide
- replacement therapy
- big data
- artificial intelligence
- mesenchymal stem cells
- copy number
- bone marrow
- health information
- quality improvement