- Interobserver diagnostic reproducibility in advanced-stage endometrial carcinoma
-
Ho Jin Jung, Soo Yeon Lee, Jin Hwa Hong, Yi Kyeong Chun
-
J Pathol Transl Med. 2021;55(1):43-52. Published online December 3, 2020
-
DOI: https://doi.org/10.4132/jptm.2020.10.04
-
-
4,939
View
-
118
Download
-
5
Web of Science
-
4
Crossref
-
 Abstract
 PDF
- Background
The accurate pathologic diagnosis and subtyping of high-grade endometrial carcinoma are often problematic, due to its atypical and overlapping histopathological features.
Methods
Three pathologists reviewed 21 surgically resected cases of advancedstage endometrial carcinoma. The primary diagnosis was based only on hematoxylin and eosin stained slides. When a discrepancy arose, a secondary diagnosis was made by additional review of immunohistochemical (IHC) stains. Finally, three pathologists discussed all cases and rendered a consensus diagnosis.
Results
The primary diagnoses were identical in 13/21 cases (62%). The secondary diagnosis based on the addition of IHC results was concordant in four of eight discrepant cases. Among four cases with discrepancies occurring in this step, two cases subsequently reached a consensus diagnosis after a thorough discussion between three reviewers. Next-generation sequencing (NGS) study was performed in two cases in which it was difficult to distinguish between serous carcinoma and endometrioid carcinoma. Based on the sequencing results, a final diagnosis of serous carcinoma was rendered. The overall kappa for concordance between the original and consensus diagnosis was 0.566 (moderate agreement).
Conclusions
We investigated stepwise changes in interobserver diagnostic reproducibility in advanced-stage endometrial carcinoma. We demonstrated the utility of IHC and NGS study results in the histopathological diagnosis of advanced-stage endometrial carcinoma.
-
Citations
Citations to this article as recorded by  - Accuracy of endometrial sampling in the diagnosis of endometrial cancer: a multicenter retrospective analysis of the JAGO-NOGGO
Zaher Alwafai, Maximilian Heinz Beck, Sepideh Fazeli, Kathleen Gürtler, Christine Kunz, Juliane Singhartinger, Dominika Trojnarska, Dario Zocholl, David Johannes Krankenberg, Jens-Uwe Blohmer, Jalid Sehouli, Klaus Pietzner
BMC Cancer.2024;[Epub] CrossRef - Deep Learning for Grading Endometrial Cancer
Manu Goyal, Laura J. Tafe, James X. Feng, Kristen E. Muller, Liesbeth Hondelink, Jessica L. Bentz, Saeed Hassanpour
The American Journal of Pathology.2024; 194(9): 1701. CrossRef - Application of NGS molecular classification in the diagnosis of endometrial carcinoma: A supplement to traditional pathological diagnosis
Qunxian Rao, Jianwei Liao, Yangyang Li, Xin Zhang, Guocai Xu, Changbin Zhu, Shengya Tian, Qiuhong Chen, Hui Zhou, Bingzhong Zhang
Cancer Medicine.2023; 12(5): 5409. CrossRef - Risk Stratification of Endometrial Cancer Patients: FIGO Stage, Biomarkers and Molecular Classification
Jenneke C. Kasius, Johanna M. A. Pijnenborg, Kristina Lindemann, David Forsse, Judith van Zwol, Gunnar B. Kristensen, Camilla Krakstad, Henrica M. J. Werner, Frédéric Amant
Cancers.2021; 13(22): 5848. CrossRef
|
E-submission
