Literature DB >> 16515993

How well does the Gleason score predict prostate cancer death? A 20-year followup of a population based cohort in Sweden.

Ove Andrén1, Katja Fall, Lennart Franzén, Swen-Olof Andersson, Jan-Erik Johansson, Mark A Rubin.   

Abstract

PURPOSE: Adenocarcinoma of the prostate is the most common cancer among men in Western countries. Although the prognostic heterogeneity of prostate cancer is enormous, clinically insignificant aggressive prostate cancers cannot be reliably distinguished. Therefore, identifying prognostic factors is increasingly important, notably among men diagnosed with localized prostate cancer, because many of them may not require aggressive treatment.
MATERIALS AND METHODS: We analyzed a population based cohort of 253 men with early stage (T1a-b, Nx, M0) initially untreated prostate cancer diagnosed between 1977 and 1991, before PSA screening was available. Tissue samples were available for 240 patients diagnosed with transurethral resection. During complete followup through September 2003, standardized criteria were used to classify histopathological characteristics, progression and causes of death.
RESULTS: Higher Gleason grade, higher nuclear grade and larger tumor volume were independent predictors of death in prostate cancer with monotonous and statistically significant trends (p <0.05). In contrast, the level of Ki-67 - strongly correlated to Gleason score - was not an independent predictor of prostate cancer death. Given a Gleason score of 7 or greater, the probability of dying of prostate cancer was 29%. The corresponding predictive value for Gleason score 8 or greater was 48%.
CONCLUSIONS: Although a high Gleason score is a determinant of prostate cancer death, its PPV is relatively low. Thus, further efforts in finding other or complementary indicators of prostate cancer outcome are needed.

Entities:  

Mesh:

Year:  2006        PMID: 16515993     DOI: 10.1016/S0022-5347(05)00734-2

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


  55 in total

1.  Molecular sampling of prostate cancer: a dilemma for predicting disease progression.

Authors:  Andrea Sboner; Francesca Demichelis; Stefano Calza; Yudi Pawitan; Sunita R Setlur; Yujin Hoshida; Sven Perner; Hans-Olov Adami; Katja Fall; Lorelei A Mucci; Philip W Kantoff; Meir Stampfer; Swen-Olof Andersson; Eberhard Varenhorst; Jan-Erik Johansson; Mark B Gerstein; Todd R Golub; Mark A Rubin; Ove Andrén
Journal:  BMC Med Genomics       Date:  2010-03-16       Impact factor: 3.063

2.  Inflammation, focal atrophic lesions, and prostatic intraepithelial neoplasia with respect to risk of lethal prostate cancer.

Authors:  Sabina Davidsson; Michelangelo Fiorentino; Ove Andrén; Fang Fang; Lorelei A Mucci; Eberhard Varenhorst; Katja Fall; Jennifer R Rider
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-09-27       Impact factor: 4.254

3.  Prognostic value of transformer 2β expression in prostate cancer.

Authors:  Yan Diao; Dong Wu; Zhijun Dai; Huafeng Kang; Ziming Wang; Xijing Wang
Journal:  Int J Clin Exp Pathol       Date:  2015-06-01

4.  Time to prostate specific antigen (PSA) nadir may predict rapid relapse in men with metastatic castration-resistant prostate cancer (CRPC) receiving docetaxel chemotherapy.

Authors:  Betsan M Thomas; Christian Smith; Jessica Evans; Michael R Button; Satish Kumar; Nachi Palaniappan; John Staffurth; Jacob S Tanguay; Jason F Lester
Journal:  Med Oncol       Date:  2013-09-12       Impact factor: 3.064

5.  Genome-wide association study of prostate cancer mortality.

Authors:  Kathryn L Penney; Saumyadipta Pyne; Fredrick R Schumacher; Jennifer A Sinnott; Lorelei A Mucci; Peter L Kraft; Jing Ma; William K Oh; Tobias Kurth; Philip W Kantoff; Edward L Giovannucci; Meir J Stampfer; David J Hunter; Matthew L Freedman
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-10-26       Impact factor: 4.254

Review 6.  TMPRSS2-ETS fusion prostate cancer: biological and clinical implications.

Authors:  Francesca Demichelis; Mark A Rubin
Journal:  J Clin Pathol       Date:  2007-11       Impact factor: 3.411

7.  Utility of multispectral imaging in automated quantitative scoring of immunohistochemistry.

Authors:  Christopher Fiore; Dyane Bailey; Niamh Conlon; Xiaoqiu Wu; Neil Martin; Michelangelo Fiorentino; Stephen Finn; Katja Fall; Swen-Olof Andersson; Ove Andren; Massimo Loda; Richard Flavin
Journal:  J Clin Pathol       Date:  2012-03-23       Impact factor: 3.411

8.  In vivo tumor grading of prostate cancer using quantitative 111In-capromab pendetide SPECT/CT.

Authors:  Youngho Seo; Carina Mari Aparici; Matthew R Cooperberg; Badrinath R Konety; Randall A Hawkins
Journal:  J Nucl Med       Date:  2009-12-15       Impact factor: 10.057

9.  Digital pathology image analysis: opportunities and challenges.

Authors:  Anant Madabhushi
Journal:  Imaging Med       Date:  2009

10.  Determining relative importance of variables in developing and validating predictive models.

Authors:  Joseph Beyene; Eshetu G Atenafu; Jemila S Hamid; Teresa To; Lillian Sung
Journal:  BMC Med Res Methodol       Date:  2009-09-14       Impact factor: 4.615

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.