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• W3141728189 abstract "BACKGROUND The Bhagarva surrogate molecular subtype definitions classify invasive breast cancer into seven the different subgroups based on immunohistochemical (IHC) criteria according to expression levels of markers as ER, PR, HER2, EGFR and/or basal cytokeratin (CK5/6) which are different in prognosis and responsiveness to adjuvant therapy. PURPOSE The present study aimed to classify primary breast cancers and directly compares the prognostic significance of the intrinsic subtypes. METHODS The current study was conducted on 522 breast cancer patients who had surgery, but had not received neoadjuvant chemotherapy, from 2011 to 2014. The clinicopathologic characteristics were recorded. IHC staining was performed for ER, PR, HER2, Ki67, CK5/6, EGFR and D2-40 markers. All breast cancer patients were stratified according to Bhagarva criteria. The followed-up patients' survival was analyzed by using Kaplan-Meier and Log-Rank models. RESULTS The luminal A (LUMA) was observed at the highest rate (32.5%). Non-basal-like triple negative phenotype (TNB-) and Luminal A HER2-Hybrid (LAHH) were the least common (3.3% in both). LUMA and luminal B (LUMB) were significantly associated with better prognostic features compared to HER2, basal-like triple negative phenotype (TNB+) and TNB-. Statistically significant differences were demonstrated between overall survival (OS), disease-free survival (DFS) and molecular subtypes (P<0.05), of which LUMB and LUMA had the highest rate of OS and DFS being 97.2 and 93.7%; and 97.2 and 90.5%, respectively. Conversely, HER2 revealed the worst prognosis with the lowest prevalence of OS and DFS (72.5 and 69.9%, respectively). CONCLUSION The molecular subtypes had a distinct OS and DFS. The intrinsic stratification displayed inversely to clinicopathological features in breast cancer." @default.
• W3141728189 created "2021-04-13" @default.
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• W3141728189 date "2021-01-01" @default.
• W3141728189 modified "2023-09-23" @default.
• W3141728189 title "Molecular classification predicts survival for breast cancer patients in Vietnam: a single institutional retrospective analysis." @default.
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