Diagnostic Accuracy of Endometrial Sampling Methods for Determining Histologic Type and Grade in Endometrial Cancer: A Retrospective Cohort Study

子宫内膜取样方法在确定子宫内膜癌组织学类型和分级方面的诊断准确性:一项回顾性队列研究

阅读:1

Abstract

INTRODUCTION: Accurate preoperative diagnosis of histologic subtype and tumor grade is essential for optimal treatment planning. This study evaluated the diagnostic accuracy of endometrial sampling and compared it with hysteroscopy, dilation and curettage (D&C), and Pipelle biopsy in identifying the histologic subtype and tumor grade of endometrial carcinoma. MATERIALS AND METHODS: This retrospective, single-center study analyzed data from 188 women with endometrial carcinoma who underwent primary hysterectomy following initial endometrial sampling at Galilee Medical Center (2010-2024). Patients were categorized by sampling method, and histologic concordance with final hysterectomy specimens was evaluated using Kappa statistics. RESULTS:  Overall, histologic concordance for endometrial sampling for determining histologic type and grade in endometrial cancer was 83%. Hysteroscopy showed the highest accuracy for histologic subtype (91%) and tumor grading (76.9%), followed by D&C and Pipelle biopsy. Kappa analysis revealed moderate concordance for hysteroscopy (κ = 0.729) and D&C (κ = 0.731), with Pipelle biopsy showing weaker concordance (κ = 0.441). Hysteroscopy was significantly more accurate than Pipelle in detecting tumor grade (p = 0.017). CONCLUSION: Endometrial sampling is moderately accurate for determining histologic type and grade in endometrial cancer. Hysteroscopy offers the highest precision for preoperative diagnosis, particularly in assessing histologic type and grade, supporting its role as the preferred diagnostic method. Future studies integrating molecular markers with histologic evaluation hold promise for improving diagnostic accuracy and optimizing treatment outcomes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。