Open AccessPrognostic value of the Ki-67 proliferation index in patients with triple negative breast carcinoma. Preliminary report
Author(s) -
Ángel Fernández,
Aldo Reigosa,
Felipe Saldivia,
L. Chamorro Castillo,
Julio Castro
Publication year - 2020
Publication title -
investigación clínica
Language(s) - English
Resource type - Journals
ISSN - 2477-9393
DOI - 10.22209/ic.v61n2a03
Subject(s) - breast cancer , triple negative breast cancer , medicine , hazard ratio , ki 67 , oncology , univariate analysis , biomarker , univariate , proportional hazards model , cancer , survival analysis , multivariate analysis , immunohistochemistry , multivariate statistics , statistics , confidence interval , biology , mathematics , biochemistry
The Ki-67 index is a biomarker that indicates the proliferation of cancer cells and is considered an effective prognostic factor for breast cancer. However, a standard cut-off point has not yet been established for the Ki-67 index in triple negative breast carcinomas. Therefore, the objective of this retrospective study was to determine an optimal cut-off point to establish it as a more accurate prognostic factor in the triple negative molecular subtype. The immunohistochemical analysis of the Ki-67 index was performed in 98 patients with breast cancer. The survival study using the Kaplan-Meier method was used to analyze the factors related to overall survival. The cut-off points (20 and 25%) were selected from the univariate analysis because they had the highest Hazard ratio to perform the multivariate analysis. With statistical significance (p<0.001), the analysis revealed that in this series the optimal cut-off point of Ki-67 is 25%, with an independent value regarding the clinicopathological variables considered in the study. These data suggest that the optimal cut-off point at 25% is a more effective prognostic factor for triple negative phenotype breast cancer. Due to the importance of these findings, it is recommended to verify the prognostic value of Ki-67 25% in series with a greater number of patients.