Suppr超能文献

对异常有丝分裂识别的一致性较差:需要标准化且可靠的定义。

Poor agreement in recognition of abnormal mitoses: requirement for standardized and robust definitions.

作者信息

Barry M, Sinha S K, Leader M B, Kay E W

机构信息

Department of Histopathology, Beaumont Hospital, Royal College of Surgeons in Ireland, Dublin, Ireland.

出版信息

Histopathology. 2001 Jan;38(1):68-72. doi: 10.1046/j.1365-2559.2001.01034.x.

Abstract

AIMS

The finding of abnormal mitoses is a helpful feature in differentiating between benign and malignant neoplasia and has prognostic significance for some tumours. As the use of a histopathological variable is limited by the reproducibility of its recognition, we tested the interobserver agreement in the classification of abnormal mitoses among histopathologists. METHODS adn

RESULTS

Ten practising histopathologists were shown 30 potential mitotic figures and were asked to classify these as 'normal mitoses', 'abnormal mitoses' or 'not mitoses' according to the criteria each pathologist used in their routine practice. The results were analysed using kappa statistics. Overall agreement was only fair with a combined kappa of 0.31 and there was unanimous categorization of only four of 30 test items, none of which was called abnormal. The poorest result was obtained for the category 'abnormal mitosis' with only slight agreement (kappa 0.19). Agreement for the other categories varied from moderate (kappa = 0.45) for 'not a mitosis' to fair (kappa = 0.26) for 'normal mitosis'. Comparison of the results for observer pairs showed that for 12 out of the 45 possible pairings, there was no more agreement than might be expected by chance alone.

CONCLUSION

Agreement is poor among practising histopathologists in the recognition of abnormal mitoses. A standardized and robust definition is needed if diagnostic and prognostic significance is accorded to the finding of an abnormal mitosis in the context of neoplasia.

摘要

目的

发现异常有丝分裂是区分良性和恶性肿瘤的一个有用特征,并且对某些肿瘤具有预后意义。由于组织病理学变量的使用受其识别重复性的限制,我们测试了病理学家之间在异常有丝分裂分类方面的观察者间一致性。

方法与结果

向十位执业病理学家展示30个潜在的有丝分裂图像,并要求他们根据每位病理学家在日常实践中使用的标准将这些图像分类为“正常有丝分裂”、“异常有丝分裂”或“不是有丝分裂”。使用kappa统计分析结果。总体一致性仅为一般,合并kappa值为0.31,在30个测试项目中只有4个得到了一致的分类,其中没有一个被判定为异常。“异常有丝分裂”类别的结果最差,只有轻微的一致性(kappa值为0.19)。其他类别的一致性从“不是有丝分裂”的中度(kappa = 0.45)到“正常有丝分裂”的一般(kappa = 0.26)不等。对观察者对的结果进行比较表明,在45种可能的配对中,有12对的一致性并不比仅由偶然因素预期的更高。

结论

执业病理学家在识别异常有丝分裂方面的一致性较差。如果在肿瘤形成的背景下赋予异常有丝分裂的发现诊断和预后意义,则需要一个标准化且可靠的定义。

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