Can Histological Grade and Mitotic Index Replace Ki67 to Determine Luminal Breast Cancer Subtypes?
Asian Pac J Cancer Prev
; 19(1): 179-183, 2018 Jan 27.
Article
in En
| MEDLINE
| ID: mdl-29373911
ABSTRACT
Introduction:
Breast cancer can be classified into subtypes based on immunohistochemical markers, with Ki67 expression levels being used to divide luminal BC tumors in luminal A and B subtypes; however, Ki67 is not routinely determined due to a lack of standardization.Objective:
To evaluate histological grade and Eliminate the mitotic index to determine if they can be used as an alternative method to Ki67 staining for luminal subtype definition.Methods:
We evaluated estrogen receptor positive breast cancer tissue samples. Pathological analysis included determination of Ki67. A low level of Ki67 was defined as <14% positive cells.Results:
We evaluated 151 breast cancer samples; 24 (15,9%) were classified as I; 74 as HG II (49%), and 53 (35,1%) as HG III. The median value for Ki67 was 13% (range <1% - 82%) and for MI was 2 (0-12). Histological grade I tumors exhibited Ki67 values significantly lower than HG II and III tumors (Anova, Tamhane test p=0,001). A higher Ki67 value was related to a higher MI (Rho Sperman p=0,336; R2= 0,0273). ROC curve analysis determined that a MI ≥ 3 had a sensibility of 61.9% and specificity of 66.7% in predicting a high Ki67 value (≥14%) (area under the curve 0,691; p =0,0001). A HG I tumor or HG II-III with MI ≤2, had a high probability of corresponding to a LA tumor (76,3%), as defined using Ki67 expression, while the probability of a LB subtype was higher with HG II-III and a MI ≥3 (57.4%). Global discrimination was 68.1%.Conclusions:
For the LA subtype, our predictive model showed a good correlation of HG and MI with the classification based on Ki67<14%. In the LB subtype, the model showed a weak correlation; therefore Ki67 determination seems to be needed for this group of patients.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Type of study:
Prognostic_studies
Language:
En
Journal:
Asian Pac J Cancer Prev
Journal subject:
NEOPLASIAS
Year:
2018
Document type:
Article