| Literature DB >> 22540077 |
Amit V Patil1, Rajeev Singhai, Rahul S Bhamre, Vinayak W Patil.
Abstract
BACKGROUND: Biological markers that reliably predict clinical or pathological response to primary systemic therapy early during a course of chemotherapy may have considerable clinical potential. AIMS: Aims of study to evaluated changes in Ki-67 (MIB-1) labeling index and apoptotic index (AI) before, during, and after neoadjuvant anthracycline chemotherapy in breast cancer in Indian women.Entities:
Keywords: Ki-67 (MIB-1); apoptotic index; breast cancer; chemotherapy; primary systemic therapy; prognostic factor; proliferative labeling index
Year: 2011 PMID: 22540077 PMCID: PMC3336898 DOI: 10.4297/najms.2011.3119
Source DB: PubMed Journal: N Am J Med Sci ISSN: 1947-2714
Fig. 1Immunohistochemical determination of mouse anti-Ki-67 using MIB-1 monoclonal primary antibody (magnification X400): [a] all dark brown nuclei shown high proliferation index and [b] low proliferation index in invasive duct breast cancer.
Patient characteristics
Fig. 2Changes in Ki-67 LI during treatment and clinical and pathological response. The data are expressed as % change between initial biopsy and day 21 relative to the initial biopsy score (x-axis) versus % change between day 21 and surgery relative to the day 21 index. (●) represents patients with a complete clinical response, () with a partial response and (○) represents no response. The asterisks represent those patients who achieved a pathological response.
Fig. 3Changes in apoptotic LI during treatment and clinical and pathological response. The data are expressed as % change between initial biopsy and day 21 relative to the initial biopsy score (x-axis) versus % change between day 21 and surgery relative to the day 21 index. (●) represents patients with a complete clinical response, () with a partial response and (○) represents no response. The asterisks represent those patients who achieved a pathological response.
Logistic regression analysis showing significant associations for prediction of response by different modalities of assessment and response classifications