Objectives: Positive resection margins after breast-conserving surgery (BCS) most often demands a repeat surgery. To preoperatively identify patients at risk of positive margins, a multivariable model has been developed that predicts positive margins after BCS with a high accuracy. This study aimed to externally validate this prediction model to explore its generalizability and assess if additional preoperatively available variables can further improve its predictive accuracy.
View Article and Find Full Text PDFPurpose: Resilience has been suggested as an important predictor of both physical and mental health-related quality of life in breast cancer patients. However, it is unclear why resilient women handle their diagnosis better, not only mentally, but also physically. The aim of this study was to investigate paths between resilience, physical activity, and mental, physical, and global health-related quality of life in breast cancer patients.
View Article and Find Full Text PDFImportance: In patients with clinically node-negative (cN0) breast cancer and 1 or 2 sentinel lymph node (SLN) macrometastases, omitting completion axillary lymph node dissection (CALND) is standard. High nodal burden (≥4 axillary nodal metastases) is an indication for intensified treatment in luminal breast cancer; hence, abstaining from CALND may result in undertreatment.
Objective: To develop a prediction model for high nodal burden in luminal ERBB2-negative breast cancer (all histologic types and lobular breast cancer separately) without CALND.
Introduction: Patients with clinically node-negative breast cancer have a negative sentinel lymph node status (pN0) in approximately 75% of cases and the necessity of routine surgical nodal staging by sentinel lymph node biopsy (SLNB) has been questioned. Previous prediction models for pN0 have included postoperative variables, thus defeating their purpose to spare patients non-beneficial axillary surgery. We aimed to develop a preoperative prediction model for pN0 and to evaluate the contribution of mammographic breast density and mammogram features derived by artificial intelligence for de-escalation of SLNB.
View Article and Find Full Text PDFBackground: Health-related quality of life and patient-related outcome measures for patients with cancer have gained increased interest over the last decade. However, few prospective studies with longitudinal data evaluated health-related quality of life in patients with breast cancer. This study aimed to investigate how health-related quality of life changed from the time of diagnosis to 1 year after breast cancer surgery for the main surgical techniques.
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