Description

Breast cancer is the most prevalent malignancy among women globally, leading to surgical interventions for non-metastatic cases. While breast cancer generally has a favorable prognosis, achieving negative resection margins at initial surgery is crucial for optimal outcomes. The challenge associated with accurately predicting the extent of resection preoperatively, as failure to secure clear margins may necessitate further resection or total mastectomy, resulting in increased psychological stress, higher healthcare costs, compromised cosmetic results, and potential negative impacts on long-term prognosis and quality of life. Many factors contribute to predicting the optimal resection extent, including imaging studies, physical examination findings, tumor molecular subtypes, presence and extent of intraductal carcinoma components, etc. Despite the availability of these predictive factors, their integration and practical application in clinical decision-making remain challenging. This prospective observational study aims to address this gap by analyzing the interplay of these factors in real-world clinical settings, with the primary objective of deriving an integrated predictive model to guide surgeons in determining the optimal extent of resection preoperatively.