Literature DB >> 7524306

Grading prostate cancer.

D G Bostwick1.   

Abstract

Histologic tumor grade is a strong predictor of outcome for men with prostate cancer. All existing grading systems successfully identify well-differentiated cancer, which progresses slowly, and poorly differentiated cancer, which progresses rapidly, but they are less successful in subdividing most moderately differentiated cancers, which have an intermediate malignant potential. The Gleason system, the de facto standard for grading, identifies histologic patterns by the degree of glandular differentiation without relying on morphogenetic or histogenetic models; it reflects tumor heterogeneity by combining primary and secondary patterns into a cancer score. Modifications that have been proposed for Gleason grading include morphometric nuclear grading, grouping of grades, estimating the amount of high-grade cancer (Gleason patterns 4 and 5), and including the cribriform pattern as Gleason pattern 4 rather than 3. Most variants of prostate cancer are high grade (Gleason patterns 4 and 5), including small cell undifferentiated carcinoma, signet ring cell carcinoma, sarcomatoid carcinoma, and carcinosarcoma. The Gleason system can be reproduced by most investigators, although there is a small but significant level of interobserver and intraobserver variability that is unavoidable. When compared with matched prostatectomy specimens, contemporary 18-gauge needle core biopsy underestimates tumor grade in 33% to 45% of cases and overestimates grade in 4% to 32% of cases, similar to results with traditional 14-gauge biopsies. Grading errors are common in biopsy specimens with small amounts of tumor and low-grade tumor, and are probably due to tissue sampling error and tumor heterogeneity. Upgrading of prostate cancer may occur after radiation therapy but is common after androgen-deprivation therapy. Univariate and multivariate analyses of prognosis in prostate cancer almost always identify cancer grade as one of the most significant predictors of patient outcome. The combination of cancer grade with other prognostic variables to create a multiple prognostic index should allow greater precision in predicting outcome for individual patients.

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Year:  1994        PMID: 7524306

Source DB:  PubMed          Journal:  Am J Clin Pathol        ISSN: 0002-9173            Impact factor:   2.493


  22 in total

1.  Improving the reproducibility of the Gleason scores in small foci of prostate cancer--suggestion of diagnostic criteria for glandular fusion.

Authors:  B Helpap; G Kristiansen; M Beer; J Köllermann; U Oehler; A Pogrebniak; Ch Fellbaum
Journal:  Pathol Oncol Res       Date:  2011-12-17       Impact factor: 3.201

2.  Monitoring response, prediction methodology, staging, and imaging in prostate cancer.

Authors:  David Pomerantz; Nicholas Vogelzang
Journal:  Rev Urol       Date:  2006

3.  The significance of modified Gleason grading of prostatic carcinoma in biopsy and radical prostatectomy specimens.

Authors:  Burkhard Helpap; Lars Egevad
Journal:  Virchows Arch       Date:  2006-11-08       Impact factor: 4.064

4.  Biopsy Detected Gleason Pattern 5 is Associated with Recurrence, Metastasis and Mortality in a Cohort of Men with High Risk Prostate Cancer.

Authors:  Sean P Stroup; Daniel M Moreira; Zinan Chen; Lauren Howard; Jonathan H Berger; Martha K Terris; William J Aronson; Matthew R Cooperberg; Christopher L Amling; Christopher J Kane; Stephen J Freedland
Journal:  J Urol       Date:  2017-07-11       Impact factor: 7.450

5.  Predicting the risk of harboring high-grade disease for patients diagnosed with prostate cancer scored as Gleason ≤ 6 on biopsy cores.

Authors:  Thomas Seisen; Françoise Roudot-Thoraval; Pierre Olivier Bosset; Aurélien Beaugerie; Yves Allory; Dimitri Vordos; Claude-Clément Abbou; Alexandre De La Taille; Laurent Salomon
Journal:  World J Urol       Date:  2014-07-02       Impact factor: 4.226

6.  Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS.

Authors:  Pallavi Tiwari; John Kurhanewicz; Anant Madabhushi
Journal:  Med Image Anal       Date:  2012-12-13       Impact factor: 8.545

7.  Statistical Shape Model for Manifold Regularization: Gleason grading of prostate histology.

Authors:  Rachel Sparks; Anant Madabhushi
Journal:  Comput Vis Image Underst       Date:  2013-09-01       Impact factor: 3.876

8.  Investigation of risk factors for prostate cancer patients with bone metastasis based on clinical data.

Authors:  Yoshiaki Yamada; Katsuya Naruse; Kogenta Nakamura; Tomohiro Taki; Motoi Tobiume; Kenji Zennami; Genya Nishikawa; Youko Itoh; Yoshitaka Muramatsu; Hiroshi Nanaura; Miho Nishimura; Kazuko Takii; Adnan Odhafa Kh Adham; Nobuaki Honda
Journal:  Exp Ther Med       Date:  2010-07-01       Impact factor: 2.447

9.  Glutathione peroxidase 1 (GPX1) genetic polymorphism, erythrocyte GPX activity, and prostate cancer risk.

Authors:  Zorica Arsova-Sarafinovska; Nadica Matevska; Ayse Eken; Daniel Petrovski; Saso Banev; Sonja Dzikova; Vladimir Georgiev; Aleksandar Sikole; Onur Erdem; Ahmet Sayal; Ahmet Aydin; Aleksandar J Dimovski
Journal:  Int Urol Nephrol       Date:  2008-06-19       Impact factor: 2.370

10.  Digital pathology image analysis: opportunities and challenges.

Authors:  Anant Madabhushi
Journal:  Imaging Med       Date:  2009
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