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Background/Aim: There are few models predicting breast cancer prognosis among patients receiving neoadjuvant chemotherapy (NAC) for estrogen receptor (ER)-positive/ human epidermal growth factor receptor 2 (HER2)-negative (luminal) breast cancer. We examined whether biological features (BFs) of residual tumors are prognostic factors following NAC. Patients and Methods: We enrolled patients with remnant tumors following NAC for luminal breast cancer and evaluated clinical stage, pathological stage, BFs prior to NAC, and BFs following NAC as prognostic factors. BFs were divided into high and low risk using the previously reported YR-IHC4 model calculated according to ER, progesterone receptor (PgR), HER2, and the proliferation marker Ki-67. Results: A total of 57 patients were enrolled in the current study. We observed a statistically significant difference in relapse-free survival (RFS) between the BF risk categories via YR-IHC4 predictions following NAC (p=0.044). The 5-year RFS rates of the BF low- and high-risk groups following NAC were 84.2% and 52.5%, respectively. Conclusion: BFs of residual tumors following NAC may be important prognostic factors in luminal breast cancer. [ABSTRACT FROM AUTHOR]

Background/Aim: Oncotype DX recurrence score (RS) for breast cancer is a useful tool for determining chemotherapy indication but it is expensive and time-consuming. We determined whether four immuno-histochemical markers, namely human epidermal growth factor 2 (HER2), estrogen receptor (ER), progesterone receptor (PgR), and Ki-67, are predictive of an RS ≥26 in Japanese patients. Patients and Methods: The study included 95 Japanese patients evaluated for RS. A predictive model was created using logistic regression analysis. Results: The discriminant function was calculated as follows: p=1/{1+exp [-(4.611+1.2342×HER2-0.0813×ER-0.0489 ×PgR+0.0857×Ki67)]}. Using a probability of 0.5 as the cutoff, the accuracy, sensitivity, specificity, positive predictive and negative predictive values were 90.5%, 72.2%, 94.8%, 76.4% and 93.5%, respectively. Conclusion: The model had a high negative predictive value in predicting RS ≥26 in Japanese patients, indicating that Oncotype DX testing may be omitted in patients with a negative result according to the predictive model. [ABSTRACT FROM AUTHOR]