Literature DB >> 14713782

Interobserver reproducibility of percent Gleason grade 4/5 in prostate biopsies.

Axel Glaessgen1, Hans Hamberg, Carl-Gustaf Pihl, Birgitta Sundelin, Bo Nilsson, Lars Egevad.   

Abstract

PURPOSE: Percent Gleason grade 4/5 (GG4/5) has been proposed as a predictor of prognosis in prostate cancer and it has been shown to add prognostic information to that given by Gleason score (GS). We recently noted that the interobserver reproducibility of percent GG4/5 in total prostatectomy specimens is at least as good as that of the GS. However, to our knowledge the reproducibility of percent GG4/5 in needle biopsies has not yet been investigated.
MATERIALS AND METHODS: A consecutive series of needle biopsies from 69 men with prostate cancer was reviewed. Biopsies were taken according to a standardized octant protocol. All 279 slides containing cancer were circulated among 4 genitourinary pathologists, who assessed GS and percent GG4/5. Results were compared pairwise and weighted kappa was calculated.
RESULTS: The 4 observers had a mean weighted kappa for GS and percent GG4/5 of 0.48 to 0.55 (overall mean 0.51) and 0.52 to 0.68 (overall mean 0.60), respectively. There was less disagreement in percent GG4/5 when a single biopsy was positive for cancer than when 6 or more biopsies were positive. The number of positive biopsies showed a stronger correlation with a discrepancy in percent GG4/5 than cancer length. Disagreement was worse when cribriform or fusion patterns were present.
CONCLUSIONS: Interobserver reproducibility of percent GG4/5 on prostate biopsies is at least as good as that of GS. Hence, concern about interobserver variability should not deter pathologists from using percent GG4/5. Grading appears to be most difficult when cancer is present in multiple biopsies or it contains cribriform or fusion patterns.

Entities:  

Mesh:

Year:  2004        PMID: 14713782     DOI: 10.1097/01.ju.0000108198.98598.00

Source DB:  PubMed          Journal:  J Urol        ISSN: 0022-5347            Impact factor:   7.450


  10 in total

1.  Interactive digital slides with heat maps: a novel method to improve the reproducibility of Gleason grading.

Authors:  Lars Egevad; Ferran Algaba; Daniel M Berney; Liliane Boccon-Gibod; Eva Compérat; Andrew J Evans; Rainer Grobholz; Glen Kristiansen; Cord Langner; Gina Lockwood; Antonio Lopez-Beltran; Rodolfo Montironi; Pedro Oliveira; Matthias Schwenkglenks; Ben Vainer; Murali Varma; Vincent Verger; Philippe Camparo
Journal:  Virchows Arch       Date:  2011-06-23       Impact factor: 4.064

2.  Interobserver variability in histologic evaluation of radical prostatectomy between central and local pathologists: findings of TAX 3501 multinational clinical trial.

Authors:  George J Netto; Mario Eisenberger; Jonathan I Epstein
Journal:  Urology       Date:  2010-12-13       Impact factor: 2.649

3.  Interobserver reproducibility of modified Gleason score in radical prostatectomy specimens.

Authors:  Axel Glaessgen; Hans Hamberg; Carl-Gustaf Pihl; Birgitta Sundelin; Bo Nilsson; Lars Egevad
Journal:  Virchows Arch       Date:  2004-05-20       Impact factor: 4.064

4.  Gleason grading challenges in the diagnosis of prostate adenocarcinoma: experience of a single institution.

Authors:  Sonja D Chen; Joseph L Fava; Ali Amin
Journal:  Virchows Arch       Date:  2015-11-12       Impact factor: 4.064

5.  Interobserver reproducibility of perineural invasion of prostatic adenocarcinoma in needle biopsies.

Authors:  Lars Egevad; Brett Delahunt; Hemamali Samaratunga; Toyonori Tsuzuki; Henrik Olsson; Peter Ström; Cecilia Lindskog; Tomi Häkkinen; Kimmo Kartasalo; Martin Eklund; Pekka Ruusuvuori
Journal:  Virchows Arch       Date:  2021-02-03       Impact factor: 4.064

6.  Interchangeability of light and virtual microscopy for histopathological evaluation of prostate cancer.

Authors:  Renata Zelic; Francesca Giunchi; Luca Lianas; Cecilia Mascia; Gianluigi Zanetti; Ove Andrén; Jonna Fridfeldt; Jessica Carlsson; Sabina Davidsson; Luca Molinaro; Per Henrik Vincent; Lorenzo Richiardi; Olof Akre; Michelangelo Fiorentino; Andreas Pettersson
Journal:  Sci Rep       Date:  2021-02-05       Impact factor: 4.379

7.  A deep learning system for prostate cancer diagnosis and grading in whole slide images of core needle biopsies.

Authors:  Nitin Singhal; Shailesh Soni; Saikiran Bonthu; Nilanjan Chattopadhyay; Pranab Samanta; Uttara Joshi; Amit Jojera; Taher Chharchhodawala; Ankur Agarwal; Mahesh Desai; Arvind Ganpule
Journal:  Sci Rep       Date:  2022-03-01       Impact factor: 4.379

8.  Reinventing diagnostics for personalized therapy in oncology.

Authors:  Diponkar Banerjee
Journal:  Cancers (Basel)       Date:  2010-06-02       Impact factor: 6.639

9.  Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading.

Authors:  Lars Egevad; Daniela Swanberg; Brett Delahunt; Peter Ström; Kimmo Kartasalo; Henrik Olsson; Dan M Berney; David G Bostwick; Andrew J Evans; Peter A Humphrey; Kenneth A Iczkowski; James G Kench; Glen Kristiansen; Katia R M Leite; Jesse K McKenney; Jon Oxley; Chin-Chen Pan; Hemamali Samaratunga; John R Srigley; Hiroyuki Takahashi; Toyonori Tsuzuki; Theo van der Kwast; Murali Varma; Ming Zhou; Mark Clements; Martin Eklund
Journal:  Virchows Arch       Date:  2020-06-15       Impact factor: 4.064

10.  Prostate cancer grading, time to go back to the future.

Authors:  Lars Egevad; Brett Delahunt; David G Bostwick; Liang Cheng; Andrew J Evans; Troy Gianduzzo; Markus Graefen; Jonas Hugosson; James G Kench; Katia R M Leite; Jon Oxley; Guido Sauter; John R Srigley; Pär Stattin; Toyonori Tsuzuki; John Yaxley; Hemamali Samaratunga
Journal:  BJU Int       Date:  2020-11-27       Impact factor: 5.588

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.