Suppr超能文献

银染核仁组成区嗜银蛋白在乳腺病变细针穿刺细胞学检查中的价值

Value of AgNORS in fine needle aspiration cytology of breast lesions.

作者信息

Rajeevan K, Aravindan K P, Kumari B C

机构信息

Pathology Department, Medical College, Calicut, Kerala, India.

出版信息

Indian J Pathol Microbiol. 1995 Jan;38(1):17-24.

PMID:8919465
Abstract

Silver staining Nucleolar organizer regions (AgNORs) were studied in fine needle aspirates of 48 benign and 36 malignant lesions and correlations with histological types, menstrual status, tumor size and lymph node involvement were looked for. A semiquantitative scoring system (AgNOR Score) reflecting total AgNOR area was applied to each of these parameters and compared with the standard counting method. The objectives were to examine the pattern of distribution and discriminating capacity of AgNORs in fine needle aspirates of different breast lesions and to evaluate the AgNOR scoring system as an alternative to the standard counting method. Mean AgNOR count was significantly higher in malignant (5.4; 95% CI 5.0-5.9) than benign (2.8; 95% CI 2.7-3.0) lesions. For AgNOR scores the corresponding values were: malignant 11. 2; 95% CI 10.2-12.2 and benign 5.3;95% CI 4.9-5.7. For malignant lesions, the counts and scores tend to be more in ductal carcinomas than lobular, more in premenopausal women, in tumors more than 5 cm in diameter and in cases with more than 3 lymph nodes involved. For all parameters the scoring system showed better discriminating capacity. The differences in AgNOR scores were statistically significant for tumor size and lymph node status. Multiple stepwise regression shown tumor size to be best correlated with AgNORs.

摘要

对48例良性病变和36例恶性病变的细针穿刺抽吸物进行了银染核仁组织区(AgNORs)研究,并寻找其与组织学类型、月经状态、肿瘤大小和淋巴结受累情况的相关性。将反映总AgNOR面积的半定量评分系统(AgNOR评分)应用于上述各项参数,并与标准计数方法进行比较。目的是研究不同乳腺病变细针穿刺抽吸物中AgNORs的分布模式和鉴别能力,并评估AgNOR评分系统作为标准计数方法的替代方法。恶性病变的平均AgNOR计数(5.4;95%可信区间5.0 - 5.9)显著高于良性病变(2.8;95%可信区间2.7 - 3.0)。AgNOR评分的相应值为:恶性11.2;95%可信区间10.2 - 12.2,良性5.3;95%可信区间4.9 - 5.7。对于恶性病变,导管癌的计数和评分往往高于小叶癌,绝经前女性、直径大于5 cm的肿瘤以及累及3个以上淋巴结的病例中的计数和评分更高。对于所有参数,评分系统显示出更好的鉴别能力。AgNOR评分在肿瘤大小和淋巴结状态方面的差异具有统计学意义。多元逐步回归显示肿瘤大小与AgNORs的相关性最佳。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验