Background: Neoadjuvant therapy refers to the administration of systemic therapy, either chemotherapy or endocrine therapy, prior to definitive breast surgery. Patients who derive clinical benefit from neoadjuvant chemotherapy (NACT) include patients with high-risk breast tumors, large breast tumors, and locally advanced tumors, including those initially ineligible for surgery. The goals of NACT include rendering inoperable tumors resectable, surgical down staging for patients who prefer breast conservation, and de-escalating axillary surgery in those with clinically positive nodes.
Aim of the Study: To evaluate the response rate to neoadjuvant chemotherapy or hormonal therapy in cases of early breast cancer (T1, T2-N0, N1-M0) according to the TNM staging and to find the predictive value of the reduction of the prognostic value Ki-67 for the response to the neo-adjuvant treatment.
Patients and Methods: This prospective study was conducted at tertiary care hospital at the breast surgery unit and clinical oncology departments, Ain Shams University Hospitals from 2015 till 2017 and performed on a total of 60 female patients with newly diagnosed early breast cancer patients according to TNM staging system.
Results: During the follow-up of the patients, the current study results revealed that Ki-67was significantly decreased with significantly decreased tumor size at follow up among the studied cases. Baseline and follow up Ki-67 were lowest in complete response, followed by partial response, then stable disease and highest in progressive response, the differences statistically were significant. As a result, Ki-67 statistically had significant moderate diagnostic performance in predicting clinical responses, was highest in predicting progressive response.
Conclusion: Ki-67 is a valuable marker, as it has prognostic and predictive abilities after neoadjuvant chemotherapy. Ki-67 expression may be considered a valuable potential biomarker and add a prognostic information to that obtained from classical prognostic factors such as tumor size.