Literature DB >> 17681059

Prediction of pathological stages before prostatectomy in prostate cancer patients: analysis of 12 systematic prostate needle biopsy specimens.

Eun-Ah Park1, Hak Jong Lee, Kwang Gi Kim, Seung Hyup Kim, Sang Eun Lee, Ghee Young Choe.   

Abstract

OBJECTIVE: To identify the most reliable predictor of the pathological stage among multiple parameters obtained by performing systematic biopsies and to assess the predictive value of any identified parameters in combination with the prostate specific antigen and the Gleason scores.
METHODS: We examined 5 biopsy parameters from 12 systematic needle biopsy results in 104 consecutive prostate cancer patients who underwent prostatectomy: the number of cores positive for cancer, percentage of positive biopsy cores, total linear cancer length (absolute sum of tumor length at each core), percentage cancer length (total cancer length divided by total length of cores obtained x100), and maximum cancer core length. The predictive values of these parameters were assessed using multivariate logistic analysis and receiver operating characteristic analysis. We evaluated whether the most reliable biopsy parameter in combination with traditional variables show better predictability of the pathological stage than traditional variables alone by receiver operating characteristic analysis.
RESULTS: Of 104 patients, 85 (82.9%) had organ confined cancer and 19 (17.1%) showed extraprostatic extension. Of the five parameters examined, maximum cancer length was found to best predict pathological staging. Although insignificant, adding results of maximum cancer length to prostate specific antigen and Gleason scores improved predictability. Of 41 patients with a maximum cancer length of <0.9 cm, PSA of <16 ng/mL, and Gleason score of <7, none showed extraprostatic extension.
CONCLUSIONS: The maximum cancer length was found to be the most reliable predictor of disease staging. The findings of a maximum cancer length of <0.9 cm, PSA of <16 ng/mL, and a Gleason score of <7 can suggest an organ-confined disease.

Entities:  

Mesh:

Year:  2007        PMID: 17681059     DOI: 10.1111/j.1442-2042.2007.01795.x

Source DB:  PubMed          Journal:  Int J Urol        ISSN: 0919-8172            Impact factor:   3.369


  5 in total

1.  Magnetic Resonance Imaging/Transrectal Ultrasonography Fusion Prostate Biopsy Significantly Outperforms Systematic 12-Core Biopsy for Prediction of Total Magnetic Resonance Imaging Tumor Volume in Active Surveillance Patients.

Authors:  Chinonyerem Okoro; Arvin K George; M Minhaj Siddiqui; Soroush Rais-Bahrami; Annerleim Walton-Diaz; Nabeel A Shakir; Jason T Rothwax; Dima Raskolnikov; Lambros Stamatakis; Daniel Su; Baris Turkbey; Peter L Choyke; Maria J Merino; Howard L Parnes; Bradford J Wood; Peter A Pinto
Journal:  J Endourol       Date:  2015-07-23       Impact factor: 2.942

2.  Pre-operative prediction of advanced prostatic cancer using clinical decision support systems: accuracy comparison between support vector machine and artificial neural network.

Authors:  Sang Youn Kim; Sung Kyoung Moon; Dae Chul Jung; Sung Il Hwang; Chang Kyu Sung; Jeong Yeon Cho; Seung Hyup Kim; Jiwon Lee; Hak Jong Lee
Journal:  Korean J Radiol       Date:  2011-08-24       Impact factor: 3.500

3.  Prediction of prostate cancer recurrence using magnetic resonance imaging and molecular profiles.

Authors:  Amita Shukla-Dave; Hedvig Hricak; Nicole Ishill; Chaya S Moskowitz; Marija Drobnjak; Victor E Reuter; Kristen L Zakian; Peter T Scardino; Carlos Cordon-Cardo
Journal:  Clin Cancer Res       Date:  2009-05-12       Impact factor: 12.531

4.  Cancer core length from targeted biopsy: an index of prostate cancer volume and pathological stage.

Authors:  Demetrios N Simopoulos; Anthony E Sisk; Alan Priester; Ely R Felker; Lorna Kwan; Merdie K Delfin; Robert E Reiter; Leonard S Marks
Journal:  BJU Int       Date:  2019-02-24       Impact factor: 5.969

5.  Combination of clinical characteristics and transrectal ultrasound-guided biopsy to predict lobes without significant cancer: application in patient selection for hemiablative focal therapy.

Authors:  Jin-Woo Jung; Byung Ki Lee; Won Suk Choi; Yong Hyun Park; Sangchul Lee; Seong Jin Jeong; Sang Eun Lee; Seok-Soo Byun
Journal:  Prostate Int       Date:  2014-03-30
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.