Content area

Abstract

Objectives

Ki67 is the most commonly used marker to evaluate proliferative index in breast cancer, however no cutoff values have been clearly defined for high ki67 index. Cancer management should be according to loco-regional profile; therefore, we aimed to determine ki67 index in 1951 cases of intrinsic breast cancer subtypes and its association with other prognostic parameters in our set up.

Results

Triple negative breast cancers showed highest ki67 index (mean 50.9 ± 23.7%) followed by Her2neu (mean 42.6 ± 21.6%) and luminal B cancers (mean 34.9 ± 20.05%). Metaplastic and medullary breast cancers significantly showed higher ki67 index as compared to ductal carcinoma, NOS. No significant association of ki67 index was noted with any of the histologic parameters in different subtypes of breast cancer expect for tumor grade. Although, ki67 index is a valuable biomarker in breast cancer, however no independent prognostic significance of ki67 could be established in our study.

Details

1009240
Title
Ki67 index in intrinsic breast cancer subtypes and its association with prognostic parameters
Publication title
Volume
12
Publication year
2019
Publication date
2019
Section
Research note
Publisher
Springer Nature B.V.
Place of publication
London
Country of publication
Netherlands
Publication subject
e-ISSN
17560500
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2019-09-23
Milestone dates
2019-02-05 (Received); 2019-09-17 (Accepted)
Publication history
 
 
   First posting date
23 Sep 2019
ProQuest document ID
2306813775
Document URL
https://www.proquest.com/scholarly-journals/ki67-index-intrinsic-breast-cancer-subtypes/docview/2306813775/se-2?accountid=208611
Copyright
© 2019. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2023-11-20
Database
ProQuest One Academic