• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

乳腺癌的组织学分级——七个病理科之间的可重复性。瑞典南部乳腺癌研究小组。

Histologic grading in breast cancer--reproducibility between seven pathologic departments. South Sweden Breast Cancer Group.

作者信息

Boiesen P, Bendahl P O, Anagnostaki L, Domanski H, Holm E, Idvall I, Johansson S, Ljungberg O, Ringberg A, Ostberg G, Fernö M

机构信息

Pathologic Department, Hospital in Helsingborg, Sweden.

出版信息

Acta Oncol. 2000;39(1):41-5. doi: 10.1080/028418600430950.

DOI:10.1080/028418600430950
PMID:10752652
Abstract

Histologic grade, including tubular formations, nuclear grade, and mitotic activity, is a well-documented prognostic factor in breast cancer. In comparison with other prognostic parameters, the evaluation of histologic grade is cheap and can be performed, in principle, in all cases of breast cancer. One possible disadvantage is that the evaluation may vary between different pathological departments. The aim of the present work was therefore to study the reproducibility of the histologic grading system by distributing haematoxylin-erythrosin-stained slides from 93 invasive breast cancers to the seven pathology departments within the southern healthcare region of Sweden. The evaluation was performed blindly and without any knowledge of other clinical parameters. In 31% of the cases the same histologic grade was obtained for all departments. The overall mean kappa was 0.54, indicating a moderate reproducibility. Of the three factors included in histologic grade, the agreement was best for tubular formations and poorest for nuclear grade and mitotic activity. The overall moderate reproducibility should be considered when the clinical usefulness of histologic grading is compared with other prognostic instruments.

摘要

组织学分级,包括管状结构、核分级和有丝分裂活性,是乳腺癌中一个有充分文献记载的预后因素。与其他预后参数相比,组织学分级评估成本低廉,原则上在所有乳腺癌病例中均可进行。一个可能的缺点是,不同病理科室之间的评估可能存在差异。因此,本研究的目的是通过将93例浸润性乳腺癌的苏木精-伊红染色切片分发给瑞典南部医疗保健区域内的七个病理科室,来研究组织学分级系统的可重复性。评估是在不知情的情况下进行的,且不了解任何其他临床参数。在31%的病例中,所有科室得出的组织学分级相同。总体平均kappa值为0.54,表明可重复性中等。在组织学分级所包含的三个因素中,管状结构的一致性最佳,核分级和有丝分裂活性的一致性最差。在将组织学分级的临床实用性与其他预后工具进行比较时,应考虑总体中等的可重复性。

相似文献

1
Histologic grading in breast cancer--reproducibility between seven pathologic departments. South Sweden Breast Cancer Group.乳腺癌的组织学分级——七个病理科之间的可重复性。瑞典南部乳腺癌研究小组。
Acta Oncol. 2000;39(1):41-5. doi: 10.1080/028418600430950.
2
Interobserver reproducibility of the Nottingham modification of the Bloom and Richardson histologic grading scheme for infiltrating ductal carcinoma.诺丁汉对浸润性导管癌的布卢姆和理查森组织学分级方案的观察者间再现性
Am J Clin Pathol. 1995 Feb;103(2):195-8. doi: 10.1093/ajcp/103.2.195.
3
Breast cancer histologic grading using digital microscopy: concordance and outcome association.数字显微镜下乳腺癌组织学分级:一致性和结果相关性。
J Clin Pathol. 2018 Aug;71(8):680-686. doi: 10.1136/jclinpath-2017-204979. Epub 2018 Mar 13.
4
Histologic grading of invasive lobular carcinoma: does use of a 2-tiered nuclear grading system improve interobserver variability?浸润性小叶癌的组织学分级:采用两级核分级系统是否能改善观察者间的变异性?
Ann Diagn Pathol. 2009 Aug;13(4):223-5. doi: 10.1016/j.anndiagpath.2009.03.004. Epub 2009 May 9.
5
Validity and reproducibility of histologic diagnosis and grading for adult soft-tissue sarcomas.成人软组织肉瘤组织学诊断及分级的有效性与可重复性
Hum Pathol. 2002 Jan;33(1):111-5. doi: 10.1053/hupa.2002.30184.
6
Primary prognostic factors in invasive breast cancer with special reference to ductal carcinoma and histologic malignancy grade.浸润性乳腺癌的主要预后因素,特别涉及导管癌和组织学恶性程度分级。
Cancer. 1994 Mar 1;73(5):1438-48. doi: 10.1002/1097-0142(19940301)73:5<1438::aid-cncr2820730519>3.0.co;2-y.
7
Interobserver agreement and reproducibility in classification of invasive breast carcinoma: an NCI breast cancer family registry study.浸润性乳腺癌分类中的观察者间一致性和可重复性:一项美国国立癌症研究所乳腺癌家族登记研究
Mod Pathol. 2006 Feb;19(2):195-207. doi: 10.1038/modpathol.3800496.
8
A binary architectural grading system for uterine endometrial endometrioid carcinoma has superior reproducibility compared with FIGO grading and identifies subsets of advance-stage tumors with favorable and unfavorable prognosis.与国际妇产科联盟(FIGO)分级相比,一种用于子宫内膜样子宫内膜癌的二元结构分级系统具有更高的可重复性,并能识别出预后良好和不良的晚期肿瘤亚组。
Am J Surg Pathol. 2000 Sep;24(9):1201-8. doi: 10.1097/00000478-200009000-00002.
9
Morphometrical malignancy grading is a valuable prognostic factor in invasive ductal breast cancer.形态学恶性肿瘤分级是浸润性导管癌中一个有价值的预后因素。
Br J Cancer. 2002 Nov 18;87(11):1275-80. doi: 10.1038/sj.bjc.6600617.
10
Histologic grading of breast carcinoma. A reproducibility study.乳腺癌的组织学分级。一项重复性研究。
Cancer. 1994 Jun 1;73(11):2765-70. doi: 10.1002/1097-0142(19940601)73:11<2765::aid-cncr2820731119>3.0.co;2-k.

引用本文的文献

1
Modification of the nuclear pleomorphism score in the Modified Bloom-Richardson grading for invasive breast cancer.浸润性乳腺癌改良 Bloom-Richardson 分级中核多形性评分的修改
PLoS One. 2025 Jul 18;20(7):e0327860. doi: 10.1371/journal.pone.0327860. eCollection 2025.
2
Breast cancer survival prediction using an automated mitosis detection pipeline.基于自动化有丝分裂检测流水线的乳腺癌生存预测。
J Pathol Clin Res. 2024 Nov;10(6):e70008. doi: 10.1002/2056-4538.70008.
3
AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer.
基于人工智能的常规苏木精-伊红(H&E)图像的早期腔面型乳腺癌预后标志物
NPJ Precis Oncol. 2023 Nov 15;7(1):122. doi: 10.1038/s41698-023-00472-y.
4
Assessment of nuclear grade-based recurrence risk classification in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative, node-positive high-risk early breast cancer.基于核分级的激素受体阳性、人表皮生长因子受体 2 阴性、淋巴结阳性高危早期乳腺癌患者复发风险分类评估。
Breast Cancer. 2023 Nov;30(6):1054-1064. doi: 10.1007/s12282-023-01500-2. Epub 2023 Aug 23.
5
Deep learning supported mitoses counting on whole slide images: A pilot study for validating breast cancer grading in the clinical workflow.深度学习支持的全切片图像有丝分裂计数:在临床工作流程中验证乳腺癌分级的初步研究。
J Pathol Inform. 2023 May 4;14:100316. doi: 10.1016/j.jpi.2023.100316. eCollection 2023.
6
Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer.计算病理学改善了早期雌激素受体阳性乳腺癌多基因检测的风险分层。
NPJ Breast Cancer. 2023 May 17;9(1):40. doi: 10.1038/s41523-023-00545-y.
7
An miRNA Signature Predicts Grading of Pancreatic Neuroendocrine Neoplasms.miRNA 特征可预测胰腺神经内分泌肿瘤的分级。
Cancer Genomics Proteomics. 2023 Mar-Apr;20(2):154-164. doi: 10.21873/cgp.20370.
8
Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology.用于评估病理学人工智能解决方案的测试数据集编制建议。
Mod Pathol. 2022 Dec;35(12):1759-1769. doi: 10.1038/s41379-022-01147-y. Epub 2022 Sep 10.
9
Progress on deep learning in digital pathology of breast cancer: a narrative review.乳腺癌数字病理学中深度学习的进展:一篇综述
Gland Surg. 2022 Apr;11(4):751-766. doi: 10.21037/gs-22-11.
10
Development and reliability of the histological THROMBEX-classification rule for thrombotic emboli of acute ischemic stroke patients.急性缺血性中风患者血栓性栓子的组织学THROMBEX分类规则的制定与可靠性
Neurol Res Pract. 2021 Sep 20;3(1):50. doi: 10.1186/s42466-021-00149-6.