External validation and evaluation of the new five-tiered prostate cancer grading system for the radical prostatectomy population in Korea

2017 ◽  
Vol 16 (10) ◽  
pp. e2640
Author(s):  
S. Yoo ◽  
M.H. Cho ◽  
J. Park ◽  
H. Jeong ◽  
M.C. Cho
The Prostate ◽  
2016 ◽  
Vol 77 (3) ◽  
pp. 263-273 ◽  
Author(s):  
Paolo Dell'Oglio ◽  
Robert Jeffrey Karnes ◽  
Giorgio Gandaglia ◽  
Nicola Fossati ◽  
Armando Stabile ◽  
...  

2016 ◽  
Vol 140 (10) ◽  
pp. 1140-1152 ◽  
Author(s):  
Oleksandr N. Kryvenko ◽  
Jonathan I. Epstein

Since 1966, when Donald Gleason, MD, first proposed grading prostate cancer based on its histologic architecture, there have been numerous changes in clinical and pathologic practices relating to prostate cancer. Patterns 1 and 2, comprising more than 30% of cases in the original publications by Gleason, are no longer reported on biopsy and are rarely diagnosed on radical prostatectomy. Many of these cases may even have been mimickers of prostate cancer that were described later with the use of contemporary immunohistochemistry. The original Gleason system predated many newly described variants of prostate cancer and our current concept of intraductal carcinoma. Gleason also did not describe how to report prostate cancer on biopsy with multiple cores of cancer or on radical prostatectomy with separate tumor nodules. To address these issues, the International Society of Urological Pathology first made revisions to the grading system in 2005, and subsequently in 2014. Additionally, a new grading system composed of Grade Groups 1 to 5 that was first developed in 2013 at the Johns Hopkins Hospital and subsequently validated in a large multi-institutional and multimodal study was presented at the 2014 International Society of Urological Pathology meeting and accepted both by participating pathologists as well as urologists, oncologists, and radiation therapists. In the present study, we describe updates to the grading of prostate cancer along with the new grading system.


2017 ◽  
Vol 71 (6) ◽  
pp. 907-912 ◽  
Author(s):  
Won Sik Ham ◽  
Heather J. Chalfin ◽  
Zhaoyong Feng ◽  
Bruce J. Trock ◽  
Jonathan I. Epstein ◽  
...  

The Prostate ◽  
2015 ◽  
Vol 76 (5) ◽  
pp. 427-433 ◽  
Author(s):  
Oleksandr N. Kryvenko ◽  
Jonathan I. Epstein

2016 ◽  
Vol 15 (3) ◽  
pp. e431
Author(s):  
P. Dell'Oglio ◽  
N. Suardi ◽  
S. Boorjian ◽  
N. Fossati ◽  
G. Gandaglia ◽  
...  

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 5073-5073
Author(s):  
Lorenzo Dutto ◽  
Jorn H. Witt ◽  
Katarina Urbanova ◽  
Christian Wagner ◽  
Andreas Schuette ◽  
...  

5073 Background: Active surveillance is increasingly used for insignificant prostate cancer (PCa). In order to identify suitable patients, risk scores have been developed which use pre-operative factors. We evaluated the accuracy of 9 separate tools developed to identify patients harbouring insignificant PCa in 2613 patients who underwent radical prostatectomy for Gleason 3+3 PCa. We have developed and validated a novel risk score to correctly identify insignificant PCa for use in unscreened patient cohorts using non-dichotomised clinical predictors. Methods: 2799 patients who would have been candidates for AS (Gleason score 6 only) patients underwent robotic radical prostatectomy between 2006 and 2016 at a tertiary referral center. The volume and grade of tumour in the resected prostate was analysed. Inignificant PCa was defined as Gleason 3+3 only, index tumour volume <1.3 cm3 , total tumour volume <2.5 cm3 (updated ERSPC definition). 2613 patients were included in the final analysis. We computed the accuracy (specificity, sensitivity and area under the curve (AUC) of the receiver operator characteristic) of 9 predictive tools. Multivariate logistic regression with elastic net regularisation was used to develop a novel tool to predict insignificant prostate cancer using age at diagnosis, baseline PSA, TRUS volume, clinical T-stage, number of positive cores and percentage of positive cores as predictors. This tool was validated in an external cohort of 441 unscreened patients undergoing surgery for Gleason 6 PCa. Results: All of the predefined tools rated poorly as predictors of insignificant disease as none of them reached the required AUC threshold of 0.7. The new tool performed well in training and validation cohorts. Conclusions: Pre-existing predictive tools to identify indolent PCa have a poor predictive value when applied to an unscreened cohort of patients. Our novel tool shows good predictive power for insignificant PCa in this population in training and validation cohorts. The inherent selection bias due to analysis of a surgical cohort is acknowledged. [Table: see text]


Sign in / Sign up

Export Citation Format

Share Document