Clinicopathological prognostic factors for survival in patients with breast cancer: a retrospective study from a tertiary cancer centre from North-West India
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View abstract on PubMed
Summary
This summary is machine-generated.Tumor grade, lymphovascular invasion (LVSI), and perinodal extension (PNE) significantly impact breast cancer survival. Early detection and personalized treatment are crucial for improving patient outcomes.
Area Of Science
- Oncology
- Pathology
- Clinical Medicine
Background
- Breast cancer is the most common malignancy globally among women.
- Identifying prognostic indicators is vital for treatment selection, response assessment, and follow-up planning.
- This study retrospectively analyzed clinical and pathological features of breast cancer patients over 10 years to correlate them with survival.
Purpose Of The Study
- To identify significant prognostic indicators for breast cancer survival.
- To assess the correlation between clinical and pathological features and overall survival (OS).
- To determine independent prognostic variables affecting breast cancer outcomes.
Main Methods
- Retrospective analysis of 676 histopathologically confirmed breast cancer patients (2014-2023).
- Collection of clinical data, treatment details (surgery, chemotherapy, radiation).
- Utilized univariate and multivariate Cox proportional hazards models to identify prognostic variables for OS.
Main Results
- Significant univariate factors for OS included stage, grade, lymph node status, lymphovascular space invasion (LVSI), perinodal extension (PNE), and distant metastasis.
- Multivariate analysis identified tumor grade, LVSI, and PNE as significant independent prognostic factors.
- The study included patients with early (56.0%), locally advanced (40.2%), and stage IV (3.1%) breast cancer.
Conclusions
- Tumor grade, LVSI, and PNE are substantial prognostic variables associated with breast cancer survival.
- A comprehensive approach involving early detection and tailored treatments is essential for optimizing survival outcomes.
- These findings underscore the importance of specific pathological features in predicting patient prognosis.
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