Literature DB >> 31107973

Problems in the reproducibility of classification of small lung adenocarcinoma: an international interobserver study.

Angela R Shih1, Hironori Uruga1,2, Emine Bozkurtlar3, Jin-Haeng Chung4, Lida P Hariri1, Yuko Minami5, He Wang6, Akihiko Yoshizawa7, Alona Muzikansky1, Andre L Moreira8, Mari Mino-Kenudson1.   

Abstract

AIMS: The 2015 WHO classification for lung adenocarcinoma (ACA) provides criteria for adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (INV), but differentiating these entities can be difficult. As our understanding of prognostic significance increases, inconsistent classification is problematic. This study assesses agreement within an international panel of lung pathologists and identifies factors contributing to inconsistent classification. METHODS AND
RESULTS: Sixty slides of small lung ACAs were reviewed digitally by six lung pathologists in three rounds, with consensus conferences and examination of elastic stains in round 3. The panel independently reviewed each case to assess final diagnosis, invasive component size and predominant pattern. The kappa value for AIS and MIA versus INV decreased from 0.44 (round 1) to 0.30 and 0.34 (rounds 2 and 3). Interobserver agreement for invasion (AIS versus other) decreased from 0.34 (round 1) to 0.29 and 0.29 (rounds 2 and 3). The range of the measured invasive component in a single case was up to 19.2 mm among observers. Agreement was excellent in tumours with high-grade cytology and fair with low-grade cytology.
CONCLUSIONS: Interobserver agreement in small lung ACAs was fair to moderate, and improved minimally with elastic stains. Poor agreement is primarily attributable to subjectivity in pattern recognition, but high-grade cytology increases agreement. More reliable methods to differentiate histological patterns may be necessary, including refinement of the definitions as well as recognition of other features (such as high-grade cytology) as a formal part of routine assessment.
© 2019 John Wiley & Sons Ltd.

Entities:  

Keywords:  histological pattern; interobserver agreement; lung adenocarcinoma; minimally invasive adenocarcinoma

Mesh:

Year:  2019        PMID: 31107973     DOI: 10.1111/his.13922

Source DB:  PubMed          Journal:  Histopathology        ISSN: 0309-0167            Impact factor:   5.087


  5 in total

1.  Use of Computed Tomography-Guided Percutaneous Biopsy of Invasive Non-Mucinous Lung Adenocarcinoma to Predict the Degree of Histological Differentiation.

Authors:  Dehao Liu; Lichun Chen; Xiaoping Wang; Yikai Lin; Jianwei Gu
Journal:  Clin Med Insights Oncol       Date:  2022-06-07

2.  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

Review 3.  A narrative review of digital pathology and artificial intelligence: focusing on lung cancer.

Authors:  Taro Sakamoto; Tomoi Furukawa; Kris Lami; Hoa Hoang Ngoc Pham; Wataru Uegami; Kishio Kuroda; Masataka Kawai; Hidenori Sakanashi; Lee Alex Donald Cooper; Andrey Bychkov; Junya Fukuoka
Journal:  Transl Lung Cancer Res       Date:  2020-10

4.  8th Edition Tumor, Node, and Metastasis T-Stage Prognosis Discrepancies: Solid Component Diameter Predicts Prognosis Better than Invasive Component Diameter.

Authors:  Kazuhito Funai; Akikazu Kawase; Kiyomichi Mizuno; Sin Koyama; Norihiko Shiiya
Journal:  Cancers (Basel)       Date:  2020-06-15       Impact factor: 6.639

5.  Verification of the eighth edition of the UICC-TNM classification on surgically resected lung adenocarcinoma: Comparison with previous classification in a local center.

Authors:  Hiroshi Minato; Kazuyoshi Katayanagi; Hiroshi Kurumaya; Nobuhiro Tanaka; Hideki Fujimori; Yoshio Tsunezuka; Takeshi Kobayashi
Journal:  Cancer Rep (Hoboken)       Date:  2021-06-24
  5 in total

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