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纤维腺瘤的细胞学标准。逐步逻辑回归分析。

Cytologic criteria for fibroadenoma. A step-wise logistic regression analysis.

作者信息

Bottles K, Chan J S, Holly E A, Chiu S H, Miller T R

机构信息

Department of Anatomic Pathology, San Francisco General Hospital, California.

出版信息

Am J Clin Pathol. 1988 Jun;89(6):707-13. doi: 10.1093/ajcp/89.6.707.

Abstract

The authors reviewed the fine-needle aspiration biopsy smears from 62 subjects with proven fibroadenoma, 60 subjects with proven ductal carcinoma, and 42 subjects with proven fibrocystic disease. All smears were coded as to the presence or absence of the following variables: epithelial cells, stroma, honeycomb sheets, antler horn clusters, naked nuclei, nucleoli, marked cellularity, foam cells, apocrine cells, anisokaryosis, atypical nuclear hyperchromasia, single cells with cytoplasm, mitotic figures, and nuclei greater than two red blood cell diameters. Step-wise logistic regression analyses were performed to determine the variables predictive of fibroadenoma. The statistical analyses selected stroma, antler horn clusters, and marked cellularity as the key cytologic criteria to differentiate fibroadenomas from fibrocystic disease. The statistical analyses selected stroma, antler horn clusters, and honeycomb sheets as the key cytologic criteria to differentiate fibroadenoma from ductal carcinoma.

摘要

作者回顾了62例经证实为纤维腺瘤、60例经证实为导管癌以及42例经证实为纤维囊性疾病患者的细针穿刺活检涂片。所有涂片均根据以下变量的有无进行编码:上皮细胞、间质、蜂窝状片层、鹿角状细胞簇、裸核、核仁、显著细胞增多、泡沫细胞、顶泌细胞、核大小不等、非典型核深染、有细胞质的单个细胞、有丝分裂象以及直径大于两个红细胞的核。进行逐步逻辑回归分析以确定预测纤维腺瘤的变量。统计分析选择间质、鹿角状细胞簇和显著细胞增多作为区分纤维腺瘤与纤维囊性疾病的关键细胞学标准。统计分析选择间质、鹿角状细胞簇和蜂窝状片层作为区分纤维腺瘤与导管癌的关键细胞学标准。

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