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British journal of cancer · Dec 2001
Nipple aspirate cytology and pathologic parameters predict residual cancer and nodal involvement after excisional breast biopsy.
- E R Sauter, H Ehya, A Mammen, and G Klein.
- Department of Surgery, Thomas Jefferson University, Philadephia, PA 19107, USA.
- Br. J. Cancer. 2001 Dec 14; 85 (12): 1952-7.
AbstractWe previously demonstrated that abnormal nipple aspirate fluid (NAF) cytology predicted residual breast cancer (RC) and tumour size after excisional biopsy (EB), although normal NAF cytology did not exclude RC. Tumour size correlates with the risk of lymph node (LN) metastases. LN metastases provide prognostic information allowing medical and radiation oncologists to determine the need for adjuvant therapy. We hypothesized that pathologic factors known after EB, combined with NAF cytology, would predict with a high degree of accuracy the presence of RC and LN spread. NAF cytology and pathologic parameters: tumour distance from biopsy margins, multifocal and multicentric disease, sub-type of ductal carcinoma in situ (DCIS) or invasive cancer (IC), grade of DCIS or IC, tumour and specimen size, tumour and biopsy cavity location, presence or absence of extensive DCIS, and biopsy scar distance from the nipple were evaluated bivariately and then by logistic regression (LR) for their association with RC and involved LN (> or = 1 (+) LN, useful to determine chemotherapy need, and > or = 4 (+) LN, useful to determine radiation need to the chest and axilla). Data were analysed using NAF cytology alone, pathologic parameters alone, and NAF cytology and pathologic parameters combined. The combined LR model was superior in predicting residual cancer (94%) to LR models using NAF cytology (36%) or pathologic parameters (75%) alone. When only subjects with normal NAF cytology were evaluated by LR, the model was 92% sensitive in predicting RC. Tumour size and NAF cytology predicted which patients had > or = 1 (+) LN, whereas tumour and specimen size predicted which patients had > or = 4 (+) LN. We propose an algorithm which, if confirmed in a larger study, may allow clinicians to be more selective in their recommendations of re-excision breast biopsy or mastectomy.
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