Predictive models and biomarkers for survival in stage III breast cancer: a review of clinical applications and future directions

Abstract

Stage III breast cancer, characterized by locally advanced tumors and potential regional lymph node involvement, presents a formidable challenge to both patients and healthcare professionals. Accurate prediction of survival outcomes is crucial for guiding treatment decisions and optimizing patient care. This publication explores the potential clinical utility of predictive tools, encompassing genetic markers, imaging techniques, and clinical parameters, to improve survival outcome predictions in stage III breast cancer. Multimodal approaches, integrating these tools, hold the promise of delivering more precise and personalized predictions. Despite the inherent challenges, such as data standardization and genetic heterogeneity, the future offers opportunities for refinement, driven by precision medicine, artificial intelligence, and global collaboration. The goal is to empower healthcare providers to make informed treatment decisions, ultimately leading to improved survival outcomes and a brighter horizon for individuals facing this challenging disease.