Literature DB >> 31655171

Interobserver variability in breast carcinoma grading results in prognostic stage differences.

Kimmie Rabe1, Olivia L Snir2, Veerle Bossuyt3, Malini Harigopal1, Romulo Celli1, Emily S Reisenbichler4.   

Abstract

The AJCC Cancer Staging Manual 8th edition included tumor grade in the pathologic prognostic stage for breast carcinomas. Due to the known subjectivity of tumor grading, we aimed to assess the degree of interobserver agreement for invasive carcinoma grade among pathologists and determine its effect on pathologic prognostic stage. One hundred consecutive cases of invasive stage II carcinomas were independently graded twice, with an 4-week intervening wash-out period, by 6 breast pathologists utilizing established Nottingham grading criteria. Inter- and intra-observer variability was determined for overall grade and for each of the 3 scoring components. Interobserver variability was good to very good (κ range = 0.582-0.850) with even better intra-observer variability (mean κ = 0.766). Tubule score was the most reproducible element (κ = 0.588). Complete concordance was reached in 54 cases and 58 cases in rounds 1 and 2 respectively. In round 1 this resulted in different pathologic prognostic stage in only 25 of discordant cases, 18 of which were stage IA versus IB. In conclusion, grading agreement between pathologists was good to very good and discordant grades resulted in small changes to pathologic prognostic stage.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  AJCC; Breast carcinoma; Histologic grade; Interobserver variability; Prognostic stage

Mesh:

Substances:

Year:  2019        PMID: 31655171     DOI: 10.1016/j.humpath.2019.09.006

Source DB:  PubMed          Journal:  Hum Pathol        ISSN: 0046-8177            Impact factor:   3.466


  7 in total

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Authors:  Orhun Cig Taskin; Michelle D Reid; Pelin Bagci; Serdar Balci; Ayse Armutlu; Deniz Demirtas; Burcin Pehlivanoglu; Burcu Saka; Bahar Memis; Emine Bozkurtlar; Can Berk Leblebici; Adelina Birceanu; Yue Xue; Mert Erkan; Yersu Kapran; Arzu Baygul; Cenk Sokmensuer; Aldo Scarpa; Claudio Luchini; Olca Basturk; Volkan Adsay
Journal:  Mod Pathol       Date:  2021-12-30       Impact factor: 7.842

2.  Quantitative analysis of breast cancer tissue composition and associations with tumor subtype.

Authors:  Linnea T Olsson; Lindsay A Williams; Bentley R Midkiff; Erin L Kirk; Melissa A Troester; Benjamin C Calhoun
Journal:  Hum Pathol       Date:  2022-02-23       Impact factor: 3.526

3.  A Grading System for Invasive Pulmonary Adenocarcinoma: A Proposal From the International Association for the Study of Lung Cancer Pathology Committee.

Authors:  Andre L Moreira; Paolo S S Ocampo; Yuhe Xia; Hua Zhong; Prudence A Russell; Yuko Minami; Wendy A Cooper; Akihiko Yoshida; Lukas Bubendorf; Mauro Papotti; Giuseppe Pelosi; Fernando Lopez-Rios; Keiko Kunitoki; Dana Ferrari-Light; Lynette M Sholl; Mary Beth Beasley; Alain Borczuk; Johan Botling; Elisabeth Brambilla; Gang Chen; Teh-Ying Chou; Jin-Haeng Chung; Sanja Dacic; Deepali Jain; Fred R Hirsch; David Hwang; Sylvie Lantuejoul; Dongmei Lin; John W Longshore; Noriko Motoi; Masayuki Noguchi; Claudia Poleri; Natasha Rekhtman; Ming-Sound Tsao; Erik Thunnissen; William D Travis; Yasushi Yatabe; Anja C Roden; Jillian B Daigneault; Ignacio I Wistuba; Keith M Kerr; Harvey Pass; Andrew G Nicholson; Mari Mino-Kenudson
Journal:  J Thorac Oncol       Date:  2020-06-17       Impact factor: 15.609

4.  Utility of Newly Proposed Grading System From International Association for the Study of Lung Cancer for Invasive Lung Adenocarcinoma.

Authors:  Atsushi Kagimoto; Yasuhiro Tsutani; Takahiro Kambara; Yoshinori Handa; Takashi Kumada; Takahiro Mimae; Kei Kushitani; Yoshihiro Miyata; Yukio Takeshima; Morihito Okada
Journal:  JTO Clin Res Rep       Date:  2020-11-26

5.  The prognostic impact of lung adenocarcinoma predominance classification relating to pathological factors in lobectomy, the Japanese Joint Committee of Lung Cancer Registry Database in 2010.

Authors:  Hiroyuki Ito; Hiroshi Date; Yasushi Shintani; Etsuo Miyaoka; Ryoichi Nakanishi; Mitsutaka Kadokura; Shunsuke Endo; Masayuki Chida; Ichiro Yoshino; Hidemi Suzuki
Journal:  BMC Cancer       Date:  2022-08-10       Impact factor: 4.638

Review 6.  Deep learning in cancer diagnosis, prognosis and treatment selection.

Authors:  Khoa A Tran; Olga Kondrashova; Andrew Bradley; Elizabeth D Williams; John V Pearson; Nicola Waddell
Journal:  Genome Med       Date:  2021-09-27       Impact factor: 11.117

Review 7.  Grading of invasive breast carcinoma: the way forward.

Authors:  C van Dooijeweert; P J van Diest; I O Ellis
Journal:  Virchows Arch       Date:  2021-07-01       Impact factor: 4.535

  7 in total

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