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.
| Original language | English |
|---|---|
| Pages (from-to) | 179-183 |
| Number of pages | 5 |
| Journal | Asian Pacific Journal of Cancer Prevention |
| Volume | 19 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Jan 2018 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Breast neoplasms
- Histology
- Ki67 antigen
- Mitotic index
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