Literature DB >> 16899486

EU-USA pathology panel for uniform diagnosis in randomised controlled trials for HRCT screening in lung cancer.

F B Thunnissen1, K M Kerr, E Brambilla, C E Comin, W A Franklin, B Guldhammerskov, W H Westra, D B Flieder.   

Abstract

Randomised controlled trials for lung cancer screening using high-resolution computed tomography are now underway. In order to allow effective future comparison of the different trials, as well as strengthening conclusions based upon the analysis of larger data sets, uniformity and consistency of pathology diagnosis are essential. The aim of the present study was to determine the effectiveness of the learning process in this difficult area of diagnostic pathology. Eight pathologists received two CD-ROMs, each with digital images of 30 cases. After diagnosing the first series, selected background reading was provided. Kappa (kappa) scores were calculated for each pathologist and category, and were compared to the consensus score. The readings of the first series showed a moderate agreement kappa score: mean+/-sd for category numbers 8 (all eight categories) and 2 were 0.53+/-0.05 and 0.65+/-0.04, respectively. The kappa 2 score distinguished between categories denoting benign and malignant lesions. The second series resulted in a good agreement kappa score: 0.65+/-0.06 for category number 8 and 0.81+/-0.02 for category number 2. In conclusion, this study demonstrates that screen-detected cases pose particular problems for pathologists and that a trained pathology panel serving randomised controlled trials is likely to lead to more consistent and accurate tissue diagnosis.

Entities:  

Mesh:

Year:  2006        PMID: 16899486     DOI: 10.1183/09031936.06.00043506

Source DB:  PubMed          Journal:  Eur Respir J        ISSN: 0903-1936            Impact factor:   16.671


  3 in total

1.  Pulmonary adenocarcinoma histology.

Authors:  Erik Thunnissen
Journal:  Transl Lung Cancer Res       Date:  2012-12

2.  Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks.

Authors:  Kun-Hsing Yu; Feiran Wang; Gerald J Berry; Christopher Ré; Russ B Altman; Michael Snyder; Isaac S Kohane
Journal:  J Am Med Inform Assoc       Date:  2020-05-01       Impact factor: 4.497

3.  Reproducibility of histopathological subtypes and invasion in pulmonary adenocarcinoma. An international interobserver study.

Authors:  Erik Thunnissen; Mary Beth Beasley; Alain C Borczuk; Elisabeth Brambilla; Lucian R Chirieac; Sanja Dacic; Douglas Flieder; Adi Gazdar; Kim Geisinger; Philip Hasleton; Yuichi Ishikawa; Keith M Kerr; Sylvie Lantejoul; Yoshiro Matsuno; Yuko Minami; Andre L Moreira; Noriko Motoi; Andrew G Nicholson; Masayuki Noguchi; Daisuke Nonaka; Giuseppe Pelosi; Iver Petersen; Natasha Rekhtman; Victor Roggli; William D Travis; Ming S Tsao; Ignacio Wistuba; Haodong Xu; Yasushi Yatabe; Maureen Zakowski; Birgit Witte; Dirk Joop Kuik
Journal:  Mod Pathol       Date:  2012-07-20       Impact factor: 7.842

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.