- A multicenter study of interobserver variability in pathologic diagnosis of papillary breast lesions on core needle biopsy with WHO classification
-
Hye Ju Kang, Sun Young Kwon, Ahrong Kim, Woo Gyeong Kim, Eun Kyung Kim, Ae Ree Kim, Chungyeul Kim, Soo Kee Min, So Young Park, Sun Hee Sung, Hye Kyoung Yoon, Ahwon Lee, Ji Shin Lee, Hyang Im Lee, Ho Chang Lee, Sung Chul Lim, Sun Young Jun, Min Jung Jung, Chang Won Jung, Soo Youn Cho, Eun Yoon Cho, Hye Jeong Choi, So Yeon Park, Jee Yeon Kim, In Ae Park, Youngmee Kwon
-
J Pathol Transl Med. 2021;55(6):380-387. Published online October 6, 2021
-
DOI: https://doi.org/10.4132/jptm.2021.07.29
-
-
5,430
View
-
210
Download
-
4
Web of Science
-
5
Crossref
-
Abstract
PDF Supplementary Material
- Background
Papillary breast lesions (PBLs) comprise diverse entities from benign and atypical lesions to malignant tumors. Although PBLs are characterized by a papillary growth pattern, it is challenging to achieve high diagnostic accuracy and reproducibility. Thus, we investigated the diagnostic reproducibility of PBLs in core needle biopsy (CNB) specimens with World Health Organization (WHO) classification.
Methods Diagnostic reproducibility was assessed using interobserver variability (kappa value, κ) and agreement rate in the pathologic diagnosis of 60 PBL cases on CNB among 20 breast pathologists affiliated with 20 medical institutions in Korea. This analysis was performed using hematoxylin and eosin (H&E) staining and immunohistochemical (IHC) staining for cytokeratin 5 (CK5) and p63. The pathologic diagnosis of PBLs was based on WHO classification, which was used to establish simple classifications (4-tier, 3-tier, and 2-tier).
Results On WHO classification, H&E staining exhibited ‘fair agreement’ (κ = 0.21) with a 47.0% agreement rate. Simple classifications presented improvement in interobserver variability and agreement rate. IHC staining increased the kappa value and agreement rate in all the classifications. Despite IHC staining, the encapsulated/solid papillary carcinoma (EPC/SPC) subgroup (κ = 0.16) exhibited lower agreement compared to the non-EPC/SPC subgroup (κ = 0.35) with WHO classification, which was similar to the results of any other classification systems.
Conclusions Although the use of IHC staining for CK5 and p63 increased the diagnostic agreement of PBLs in CNB specimens, WHO classification exhibited a higher discordance rate compared to any other classifications. Therefore, this result warrants further intensive consensus studies to improve the diagnostic reproducibility of PBLs with WHO classification.
-
Citations
Citations to this article as recorded by 
- Beyond the benign: A rare case report of myxoid pleomorphic liposarcoma
Arslan Ahmad, Muhammad Ammar, Muhammad Hasnain Saleem Choudary, Muhammad Nouman Sadiq, Rana Uzair Ahmad, Nouman Aziz Radiology Case Reports.2025; 20(5): 2500. CrossRef - Invasive papillary carcinoma of the breast
Shijing Wang, Qingfu Zhang, Xiaoyun Mao Frontiers in Oncology.2024;[Epub] CrossRef - Recommendations for Performance Evaluation of Machine Learning in Pathology: A Concept Paper From the College of American Pathologists
Matthew G. Hanna, Niels H. Olson, Mark Zarella, Rajesh C. Dash, Markus D. Herrmann, Larissa V. Furtado, Michelle N. Stram, Patricia M. Raciti, Lewis Hassell, Alex Mays, Liron Pantanowitz, Joseph S. Sirintrapun, Savitri Krishnamurthy, Anil Parwani, Giovann Archives of Pathology & Laboratory Medicine.2024; 148(10): e335. CrossRef - Encapsulated papillary carcinoma of the breast: A single institution experience
Liang Xu, Qixin Mao, Qiuming Liu, Yufeng Gao, Lihua Luo, Chungen Guo, Wei Qu, Ningning Yan, Yali Cao Oncology Letters.2023;[Epub] CrossRef - High-risk and selected benign breast lesions diagnosed on core needle biopsy: Evidence for and against immediate surgical excision
Aparna Harbhajanka, Hannah L. Gilmore, Benjamin C. Calhoun Modern Pathology.2022; 35(11): 1500. CrossRef
- Myoferlin Expression and Its Correlation with FIGO Histologic Grading in Early-Stage Endometrioid Carcinoma
-
Min Hye Kim, Dae Hyun Song, Gyung Hyuck Ko, Jeong Hee Lee, Dong Chul Kim, Jung Wook Yang, Hyang Im Lee, Hyo Jung An, Jong Sil Lee
-
J Pathol Transl Med. 2018;52(2):93-97. Published online March 14, 2018
-
DOI: https://doi.org/10.4132/jptm.2017.11.29
-
-
6,980
View
-
117
Download
-
11
Web of Science
-
9
Crossref
-
Abstract
PDF
- Background
For endometrioid carcinoma patients, International Federation of Gynecologists and Obstetricians (FIGO) histologic grading is very important for identifying the appropriate treatment method. However, the interobserver discrepancy with this three-tiered grading system is a serious potential problem. In this study, we used immunohistochemistry to analyze the relationship between FIGO histologic grading score and myoferlin expression.
Methods We studied the endometrioid carcinoma tissues of 60 patients from Gyeongsang National University Hospital between January 2002 and December 2009. Immunohistochemical analysis of myoferlin was performed on tissue microarray blocks from surgical specimens.
Results Myoferlin expression was observed in 58 of 60 patients. Moderate and strong myoferlin expression was observed in low-grade endometrioid carcinoma, while there was a tendency toward loss of myoferlin expression in high-grade endometrioid carcinoma (p<.001).
Conclusions Our study revealed that myoferlin loss is significantly correlated with high FIGO grade of endometrioid carcinoma.
-
Citations
Citations to this article as recorded by 
- Myoferlin: A Potential Marker of Response to Radiation Therapy and Survival in Locally Advanced Rectal Cancer
Hayley Fowler, Rachael E. Clifford, David Bowden, Paul A. Sutton, Naren Govindarajah, Matthew Fok, Mark Glenn, Michael Wall, Carlos Rubbi, Simon J.A. Buczacki, Amit Mandal, Hayley Francies, Jonathan Hughes, Jason L. Parsons, Dale Vimalachandran International Journal of Radiation Oncology*Biology*Physics.2024; 120(4): 1111. CrossRef - Neoexpression of JUNO in Oral Tumors Is Accompanied with the Complete Suppression of Four Other Genes and Suggests the Application of New Biomarker Tools
Dominik Kraus, Simone Weider, Rainer Probstmeier, Jochen Winter Journal of Personalized Medicine.2022; 12(3): 494. CrossRef - Correlation between myoferlin expression and lymph node metastasis in papillary thyroid carcinoma
Ji Min Na, Dong Chul Kim, Dae Hyun Song, Hyo Jung An, Hyun Min Koh, Jeong-Hee Lee, Jong Sil Lee, Jung Wook Yang, Min Hye Kim Journal of Pathology and Translational Medicine.2022; 56(4): 199. CrossRef - PINCH-1 interacts with myoferlin to promote breast cancer progression and metastasis
Tao Qian, Chengmin Liu, Yanyan Ding, Chen Guo, Renwei Cai, Xiaoxia Wang, Rong Wang, Kuo Zhang, Li Zhou, Yi Deng, Chuanyue Wu, Ying Sun Oncogene.2020; 39(10): 2069. CrossRef - Human colon cancer cells highly express myoferlin to maintain a fit mitochondrial network and escape p53-driven apoptosis
Gilles Rademaker, Brunella Costanza, Justine Bellier, Michael Herfs, Raphaël Peiffer, Ferman Agirman, Naïma Maloujahmoum, Yvette Habraken, Philippe Delvenne, Akeila Bellahcène, Vincent Castronovo, Olivier Peulen Oncogenesis.2019;[Epub] CrossRef - Prognostic significance of immunohistochemical staining for myoferlin in clear cell renal cell carcinoma and its association with epidermal growth factor receptor expression
Minsun Jung, Cheol Lee, Jeong Hwan Park, Kyung Chul Moon Urologic Oncology: Seminars and Original Investigations.2019; 37(11): 812.e9. CrossRef - Ferlin Overview: From Membrane to Cancer Biology
Olivier Peulen, Gilles Rademaker, Sandy Anania, Andrei Turtoi, Akeila Bellahcène, Vincent Castronovo Cells.2019; 8(9): 954. CrossRef - Myoferlin, a multifunctional protein in normal cells, has novel and key roles in various cancers
Wei Zhu, Bolun Zhou, Chenxuan Zhao, Zhengqing Ba, Hongjuan Xu, Xuejun Yan, Weidong Liu, Bin Zhu, Lei Wang, Caiping Ren Journal of Cellular and Molecular Medicine.2019; 23(11): 7180. CrossRef - Myoferlin, a Membrane Protein with Emerging Oncogenic Roles
Yimin Dong, Honglei Kang, Huiyong Liu, Jia Wang, Qian Guo, Chao Song, Yunlong Sun, Ya Zhang, Honghua Zhang, Zheng Zhang, Hanfeng Guan, Zhong Fang, Feng Li BioMed Research International.2019; 2019: 1. CrossRef
|