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Underestimation of malignancy of breast core‐needle biopsy
Author(s) -
Houssami Nehmat,
Ciatto Stefano,
Ellis Ian,
Ambrogetti Daniela
Publication year - 2006
Publication title -
cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.052
H-Index - 304
eISSN - 1097-0142
pISSN - 0008-543X
DOI - 10.1002/cncr.22435
Subject(s) - medicine , malignancy , ductal carcinoma , confidence interval , breast cancer , biopsy , radiology , sampling (signal processing) , cancer , gynecology , filter (signal processing) , computer science , computer vision
BACKGROUND: A review of the literature indicated variable underestimation rates for breast core‐needle biopsy (CNB) based on generally small series. In this article, the authors present precise estimates for overall underestimation and for categories of histologic underestimates (including categories that reflect contemporary classification) and examine the effect of lesion and sampling variables. METHODS: Among 4035 consecutive CNBs, the authors examined women whose CNB outcome represented a potential underestimate of malignancy ( benign but of uncertain biologic or malignant potential or B3 and ductal carcinoma in situ [DCIS]). From 889 eligible women, all 758 women who had excision histology available were included. RESULTS: Overall underestimation of CNB was 27.7% (95% confidence interval [95% CI], 24.5–30.9%). The following category‐specific rates were used: B3 underestimates, 36.2% (95% CI, 30.6–41.8%); B3 underestimates (excluding atypical proliferations), 17.9% (95% CI, 10.8–24.9%); atypical ductal hyperplasia underestimates, 29.0% (95% CI, 21.4–36.6%; upgraded to DCIS) and 44.2% (95% CI, 36.0–52.5%; upgraded to DCIS or invasive cancer); and DCIS underestimates, 22.8% (95% CI, 19.0–26.5%). There was a significant trend toward greater underestimation of malignancy with increasing lesion size on imaging studies for overall underestimates ( P = .00008), B3 underestimates ( P = .009), and DCIS underestimates ( P = .0007). Underestimation rates did not differ between masses (27.9%) and microcalcifications (27.6%; chi‐square statistic with 1 degree of freedom = 3.02; P = .98) and were significantly lower for vacuum‐assisted CNB (11‐gauge) than for automated CNB (14‐gauge; P = .001). Underestimation rates, when sampling microcalcifications, decreased with increasing number of cores collected, but this was mainly for DCIS underestimates. CONCLUSIONS: CNB results that were not definitely negative or were not positive for invasive cancer were associated with high rates of underestimation of disease and with target lesion size. Identifying imaging or sampling factors that affect underestimation rates of CNB may assist in reducing their occurrence and better predicting excision histology outcomes. Cancer 2007;109:496–501. © 2006 American Cancer Society.