Impact of Ki 67 and Progesterone receptor status on the outcome of metastatic breast cancer patients treated with cyclin dependant kinase inhibitors

Faculty Medicine Year: 2024
Type of Publication: ZU Hosted Pages:
Authors:
Journal: African Journal of Biological Sciences African Society of Sustainable Development Volume:
Keywords : Impact , , , , Progesterone receptor status , , outcome of metastatic    
Abstract:
Abstract: Background: Breast cancer is the most common malignancy in females worldwide and is the second cause of cancer related mortality after lung cancer. Outcome of treatment of metastatic breast cancer is still controverse , up till now no clear data about effect of ki67 an PR status on treatment outcome. we aimed to determine the prognostic and predictive value of Ki67 and PR status among metastatic breast cancer patients on CDK4\6 inhibitor treatment. Patients and Methods: This observational prospective cohort study was conducted on 50 female patients with hormone- receptor-positive (HR+) and human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (BC) from January 2022 till May 2024 with median follow up period 19.88 months (10.89- 28.09), treated and followed up at the Department of Medical Oncology, faculty of medicine, Zagazig University. Ki67 and progesterone receptor status were assessed by immunohistochemistry in primary tumor samples before starting the treatment. Results: Considering biobsy from primary tumour, IDC was the commonest pathological type (90.0%), Grade II was the commonest (64.0%) followed by Grade III (28.5%), ER positive was the commonest (93.0%), PR ≥ 20 % was (60.0%), Ki67 ≥ 14 % was (62.0%), The biobsy from metastatic site showed that, all the studied group were ER positive (100%), PR ≥ 20 % was (62%) and ki67 Low (< 0.001). Conclusion: Outcome of treatment of metastatic breast cancer is still controverse , Ki-67 and progesterone receptor status may be reliable predictors of response to CDK4/6 inhibitors in metastatic breast cancer, highlighting the need for further research to identify robust biomarkers. Alternative predictive biomarkers and patient stratification strategies are therefore crucial for optimizing treatment selection and improving outcomes.
   
     
 
       

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