Assessing The Potential Value of KI-67 in Predicting the Therapeutic Response to Neoadjuvant Chemotherapy in Breast Cancer Patients in Indian Population and to Determine the Best Ki-67 Cutoff Value that Increases the Prediction Accuracy in Making Treatment Decisions
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Date
2024-12
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International Research Organization for Life & Health Sciences
Abstract
Objective: To assess the potential value of Ki-67 in predicting the therapeutic response to neoadjuvant chemotherapy in breast cancer patients in the Indian population and to determine the best Ki-67 cutoff value that increases the prediction accuracy in making treatment decisions. Materials and Methods: This is a prospective observational study where breast cancer patients who underwent MRM/BCS surgery after neoadjuvant chemotherapy at SSKM and IPGMER Hospital between January 2024 and September 2024 in 50 patients. The clinical and pathologic characteristics of all patients were obtained from the hospital medical records. The clinical and pathological response to chemotherapy was determined. Result: As a result of the analysis from this study, clinical and pathological responses to NST were significantly improved when Ki-67 levels were high >17% (P = 0.05). Furthermore, a better rate of pathological complete response (pCR) was significantly associated with tumor size <5 cm (P = 0.02), and vascular invasion when positive (P = 0.023). Conclusion: Clinical and pathological responses to NST were significantly improved when Ki-67 levels were high >17. Furthermore, a better rate of pCR was significantly associated with tumor size <5 cm, and vascular invasion when positive. Our analysis showed that a Ki-67 cutoff >17% predicted a better pCR rate.
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Keywords
Breast cancer, Ki-67, Neoadjuvant chemotherapy, Tumor size
Citation
Naz A, Sarkar DK, Basu S, Das AK, Roy PK. . Assessing The Potential Value of KI-67 in Predicting the Therapeutic Response to Neoadjuvant Chemotherapy in Breast Cancer Patients in Indian Population and to Determine the Best Ki-67 Cutoff Value that Increases the Prediction Accuracy in Making Treatment Decisions. International Journal of Scientific Study. 2024 Dec; 12(9): 23-28