Significance of Histomorphology of Early Triple-Negative Breast Cancer
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Triple-negative breast cancer (TNBC) is a heterogeneous disease. Possibly genetic characterisation provides the most appropriate information on tumour biology and prognosis, but it is only limitedly available in clinical practice. The aim of this investigation was to explore what additional prognostic information could be gained from detailed histomorphologic report. Patients and method: patients were selected retrospectively operated from 2005 to 2009 in one institution and charts were revised. Beyond age, tumour and nodal status, histologic grade and therapy, the additional pathologic characteristics were also involved in analysis: necrosis, lymphocytic infiltration, peritumoural vascular invasion (PVI), perineural invasion, DCIS extent and grade, perinodal spread, mitotic activity index (MAI). Results: 295 early TNBC were involved. In univariate survival analysis with a mean follow-up of 3.57 years the tumour size, the nodal status, type of operation (conservation or mastectomy), irradiation, PVI and perinodal spread proved to be significantly connected with both disease free survival (DFS) and breast cancer specific overall survival (BSOS), and necrosis and chemotherapy with BSOS. Necrosis analysed together with lymphocytic infiltrate showed greater predicting power. In multivariate analysis nodal metastasis, necrosis positive/lymphacytic infiltration negative status and lack of irradiation has significant negative impact on DFS (p = <0.0001 HR:1.98 [1.4–2.77], p = <0.017 HR:2.1 [1.1–3.8], p = <0.001 HR:0.25 [0.11–0.57], respectively) and BSOS (p = <0.0001 HR:2.47 [1.8–3.4], p = <0.017 HR:3.7 [1.6–8.2], p = <0.0017 HR:0.24 [0.1–0.58], respectively). For DFS perivascular invasion also showed significant effect (p = <0.042 HR:2.5 [1.0–6.0]). Nodal status was the strongest prognostic parameter but other histomorphologic parameters can be used for prognosis prediction.
KeywordsTriple-negative breast cancer Vascular invasion Necrosis Irradiation
We are grateful to statistician Istvan Gaudi for his unlimited support in statistical analysis and to Monika Nagy and Tibor Radovics for their help in data acquisition.
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