Background: Among women worldwide, breast cancer is the most prevalent malignancy. Understanding potential prognostic indicators is critical for selecting the optimal treatment modalities, evaluating the response and creating a follow-up plan. In this retrospective study, the clinical and pathological features of primary breast cancer patients who presented to the tertiary cancer centre in the past 10 years were retrospectively studied and analysed to assess their correlation with survival.

Patients and methods: Histopathologically confirmed breast cancer patients presenting between January 2014 and December 2023 were included in this study. Clinical data and treatment details including the surgical procedure, chemotherapy and radiation treatment were collected from the medical records. The study utilised both univariate and multivariate Cox proportional hazards models to determine the most significant independent prognostic variables for overall survival (OS).

Results: A total of 676 patients were treated for breast cancer in our centre between January 2014 and December 2023. The median age was 50 years. Three seventy nine patients (56.0%) presented with early breast cancer at the time of diagnosis while 272 patients (40.2%) had locally advanced breast cancer corresponding to clinical stage III. Twenty one (3.1%) patients presented with stage IV. In the univariate analysis, factors significantly associated with OS were stage at presentation, grade, positive lymph node status, number of positive lymph nodes, presence of lymphovascular space invasion (LVSI), presence of perinodal extension (PNE) and distant metastasis at presentation. On multivariate analysis, grade of tumor, LVSI and PNE were significant factors affecting survival outcome.

Conclusion: Clinical stage at presentation, tumour grade, lymph node status, presence of LVSI, PNE and tumour grade were the prognostic variables substantially associated with survival. A comprehensive approach that includes early detection and appropriate treatment modalities tailored to individual patient characteristics is essential for optimising survival outcomes in breast cancer patients.