Literature DB >> 12012297

Nomograms and instruments for the initial prostate evaluation: the ability to estimate the likelihood of identifying prostate cancer.

Makoto Ohori1, Peter Swindle.   

Abstract

As a result of prostate cancer screening programs, approximately 10% of otherwise healthy men will be found to have an elevated prostate-specific antigen (PSA) level and therefore be at risk for harboring prostate cancer. Patients with an elevated PSA level have a wide variation in the risk for having prostate cancer diagnosed by transrectal ultrasound (TRUS)-guided prostate biopsy. To adequately counsel these patients, some form of individualized risk assessment must be given. There are several tables, artificial neural network (ANN) models, and nomograms that are available to stratify an individual patients risk for having prostate cancer diagnosed by a TRUS biopsy, either initially or on subsequent biopsies after a previous negative biopsy. Presently, nomograms are also being developed to predict the risk not only for having prostate cancer but also for clinically significant prostate cancer. The difficulty in calculating this risk for an individual patient is that the multiple competing clinical and pathologic factors have varying degrees of effect on the overall risk. This problem of competing risk factors can be overcome by the use of nomograms or ANNs. This article reviews the available instruments that are available to the urologist to enable prediction of the risk for having prostate cancer diagnosed by TRUS-guided prostate biopsy. Copyright 2002, Elsevier Science (USA). All rights reserved.

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Year:  2002        PMID: 12012297     DOI: 10.1053/suro.2002.32520

Source DB:  PubMed          Journal:  Semin Urol Oncol        ISSN: 1081-0943


  4 in total

1.  Chinese nomogram to predict probability of positive initial prostate biopsy: a study in Taiwan region.

Authors:  Shu-Chun Kuo; Shun-Hsing Hung; Hsien-Yi Wang; Chih-Chiang Chien; Chin-Li Lu; Hung-Jung Lin; How-Ran Guo; Jian-Fang Zou; Chian-Shiung Lin; Chien-Cheng Huang
Journal:  Asian J Androl       Date:  2013-10-14       Impact factor: 3.285

Review 2.  Predicting melanoma risk: theory, practice and future challenges.

Authors:  David Whiteman
Journal:  Melanoma Manag       Date:  2014-12-04

3.  Image-based clinical decision support for transrectal ultrasound in the diagnosis of prostate cancer: comparison of multiple logistic regression, artificial neural network, and support vector machine.

Authors:  Hak Jong Lee; Sung Il Hwang; Seok-Min Han; Seong Ho Park; Seung Hyup Kim; Jeong Yeon Cho; Chang Gyu Seong; Gheeyoung Choe
Journal:  Eur Radiol       Date:  2009-12-17       Impact factor: 5.315

4.  Potential predictive factors of positive prostate biopsy in the Japanese population.

Authors:  Katsumi Shigemura; Soichi Arakawa; Kunito Yamanaka; Nobuo Yasui; Shigeji Matsubara; Takahiro Iwamoto; Nobuo Kataoka; Keiji Yuien; Masato Fujisawa
Journal:  Int Urol Nephrol       Date:  2007-07-04       Impact factor: 2.370

  4 in total

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