Literature DB >> 22393997

High Ki-67 expression is a poor prognostic indicator of 5-year recurrence free survival in patients with invasive breast cancer.

Xue-Qin Yang1, Fu-Bing Wang, Chuang Chen, Chun-Wei Peng, Jing-Fang Zhang, Yan Li.   

Abstract

OBJECTIVE: Ki-67 is a biomarker that reflects the cell proliferation state. Despite a clear understanding of the protein's structure and properties, its functional role remains elusive. We conducted the present study to assess the prognostic value of Ki-67 in breast cancer (BC).
METHODS: We enrolled 164 individuals in this study: 30 patients with benign tumors and 134 with invasive BC. Immunohistochemistry (IHC) was used to detect Ki-67 expression The prognostic value of Ki-67 for 5-year recurrence-free survival (RFS) could be analyzed in 134 BC patients.
RESULTS: Ki-67 expression showed significant differences with the tumor grade, lymph node (LN) status, HER2 status and hormone receptor (HR) status (all P<0.05). When Ki- 67 11% was used as cutoff to divide the 134 cases into two groups, with high and low expression, the patients in former had a significantly higher 5-year recurrence rate (37.1% vs 8.1%, P=0.001) and a worse RFS (log-rank test, P=0.0017) than those in low Ki-67 expression group. Ki-67 was an independent prognostic predictor of 5-year RFS in both univariate and multivariate analyses.
CONCLUSIONS: Ki-67 can be used as a negative predictor of 5-year RFS of patients with invasive BC.

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Year:  2011        PMID: 22393997

Source DB:  PubMed          Journal:  Asian Pac J Cancer Prev        ISSN: 1513-7368


  5 in total

1.  Ki-67 expression in sclerosing adenosis and adjacent normal breast terminal ductal lobular units: a nested case-control study from the Mayo Benign Breast Disease Cohort.

Authors:  Aziza Nassar; Tanya L Hoskin; Melody L Stallings-Mann; Amy C Degnim; Derek C Radisky; Marlene H Frost; Robert A Vierkant; Lynn C Hartmann; Daniel W Visscher
Journal:  Breast Cancer Res Treat       Date:  2015-04-12       Impact factor: 4.872

2.  Quantum dots-based quantitative and in situ multiple imaging on ki67 and cytokeratin to improve ki67 assessment in breast cancer.

Authors:  Jing Ping Yuan; Lin Wei Wang; Ai Ping Qu; Jia Mei Chen; Qing Ming Xiang; Chuang Chen; Sheng-Rong Sun; Dai-Wen Pang; Juan Liu; Yan Li
Journal:  PLoS One       Date:  2015-04-09       Impact factor: 3.240

3.  A Hybrid Computer-aided-diagnosis System for Prediction of Breast Cancer Recurrence (HPBCR) Using Optimized Ensemble Learning.

Authors:  Mohammad R Mohebian; Hamid R Marateb; Marjan Mansourian; Miguel Angel Mañanas; Fariborz Mokarian
Journal:  Comput Struct Biotechnol J       Date:  2016-12-06       Impact factor: 7.271

4.  PCA-PAM50 improves consistency between breast cancer intrinsic and clinical subtyping reclassifying a subset of luminal A tumors as luminal B.

Authors:  Praveen-Kumar Raj-Kumar; Jianfang Liu; Jeffrey A Hooke; Albert J Kovatich; Leonid Kvecher; Craig D Shriver; Hai Hu
Journal:  Sci Rep       Date:  2019-05-28       Impact factor: 4.379

5.  Subtype classification for prediction of prognosis of breast cancer from a biomarker panel: correlations and indications.

Authors:  Chuang Chen; Jing-Ping Yuan; Wen Wei; Yi Tu; Feng Yao; Xue-Qin Yang; Jin-Zhong Sun; Sheng-Rong Sun; Yan Li
Journal:  Int J Nanomedicine       Date:  2014-02-21
  5 in total

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