Literature DB >> 17333205

Assay-specific artificial neural networks for five different PSA assays and populations with PSA 2-10 ng/ml in 4,480 men.

Carsten Stephan1, Chuanliang Xu, Henning Cammann, Markus Graefen, Alexander Haese, Hartwig Huland, Axel Semjonow, Eleftherios P Diamandis, Mesut Remzi, Bob Djavan, Mark F Wildhagen, Bert G Blijenberg, Patrik Finne, Ulf-Hakan Stenman, Klaus Jung, Hellmuth-Alexander Meyer.   

Abstract

Use of percent free PSA (%fPSA) and artificial neural networks (ANNs) can eliminate unnecessary prostate biopsies. In a total of 4,480 patients from five centers with PSA concentrations in the range of 2-10 ng/ml an IMMULITE PSA-based ANN (iANN) was compared with other PSA assay-adapted ANNs (nANNs) to investigate the impact of different PSA assays. ANN data were generated with PSA, fPSA (assays from Abbott, Beckman, DPC, Roche or Wallac), age, prostate volume, and DRE status. In 15 different ROC analyses, the area under the curve (AUC) in the PSA ranges 2-4, 2-10, and 4-10 ng/ml for the nANN was always significantly larger than the AUC for %fPSA or PSA. The nANN and logistic regression models mostly also performed better than the iANN. Therefore, for each patient population, PSA assay-specific ANNs should be used to optimize the ANN outcome in order to reduce the number of unnecessary biopsies.

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Year:  2007        PMID: 17333205     DOI: 10.1007/s00345-006-0132-9

Source DB:  PubMed          Journal:  World J Urol        ISSN: 0724-4983            Impact factor:   4.226


  40 in total

1.  Verification bias and the prostate-specific antigen test--is there a case for a lower threshold for biopsy?

Authors:  Fritz H Schröder; Ries Kranse
Journal:  N Engl J Med       Date:  2003-07-24       Impact factor: 91.245

2.  Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial.

Authors:  W J Catalona; A W Partin; K M Slawin; M K Brawer; R C Flanigan; A Patel; J P Richie; J B deKernion; P C Walsh; P T Scardino; P H Lange; E N Subong; R E Parson; G H Gasior; K G Loveland; P C Southwick
Journal:  JAMA       Date:  1998-05-20       Impact factor: 56.272

3.  Use of percentage of free prostate-specific antigen to identify men at high risk of prostate cancer when PSA levels are 2.51 to 4 ng/mL and digital rectal examination is not suspicious for prostate cancer: an alternative model.

Authors:  W J Catalona; A W Partin; J A Finlay; D W Chan; H G Rittenhouse; R L Wolfert; D L Woodrum
Journal:  Urology       Date:  1999-08       Impact factor: 2.649

4.  An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis: results of a 5-year investigation.

Authors:  Carsten Stephan; Klaus Jung; Henning Cammann; Birgit Vogel; Brigitte Brux; Glen Kristiansen; Birgit Rudolph; Steffen Hauptmann; Michael Lein; Dietmar Schnorr; Pranav Sinha; Stefan A Loening
Journal:  Int J Cancer       Date:  2002-05-20       Impact factor: 7.396

5.  The influence of prostate volume on the ratio of free to total prostate specific antigen in serum of patients with prostate carcinoma and benign prostate hyperplasia.

Authors:  C Stephan; M Lein; K Jung; D Schnorr; S A Loening
Journal:  Cancer       Date:  1997-01-01       Impact factor: 6.860

Review 6.  Prostate specific antigen: a decade of discovery--what we have learned and where we are going.

Authors:  T J Polascik; J E Oesterling; A W Partin
Journal:  J Urol       Date:  1999-08       Impact factor: 7.450

Review 7.  Discordance of assay methods creates pitfalls for the interpretation of prostate-specific antigen values.

Authors:  A Semjonow; B Brandt; F Oberpenning; S Roth; L Hertle
Journal:  Prostate Suppl       Date:  1996

8.  Multicenter evaluation of an artificial neural network to increase the prostate cancer detection rate and reduce unnecessary biopsies.

Authors:  Carsten Stephan; Henning Cammann; Axel Semjonow; Eleftherios P Diamandis; Leon F A Wymenga; Michael Lein; Pranav Sinha; Stefan A Loening; Klaus Jung
Journal:  Clin Chem       Date:  2002-08       Impact factor: 8.327

9.  Two-year stability of free and total PSA in frozen serum samples.

Authors:  D Woodrum; L York
Journal:  Urology       Date:  1998-08       Impact factor: 2.649

10.  Prevalence of prostate cancer among men with a prostate-specific antigen level < or =4.0 ng per milliliter.

Authors:  Ian M Thompson; Donna K Pauler; Phyllis J Goodman; Catherine M Tangen; M Scott Lucia; Howard L Parnes; Lori M Minasian; Leslie G Ford; Scott M Lippman; E David Crawford; John J Crowley; Charles A Coltman
Journal:  N Engl J Med       Date:  2004-05-27       Impact factor: 91.245

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  4 in total

1.  [New serum markers in prostate carcinoma and their application to artificial neural networks].

Authors:  C Stephan; K Jung; H Cammann; J Kramer; G Kristiansen; S A Loening; M Lein
Journal:  Urologe A       Date:  2007-09       Impact factor: 0.639

Review 2.  [Value of biomarkers in urology].

Authors:  P J Goebell; B Keck; S Wach; B Wullich
Journal:  Urologe A       Date:  2010-04       Impact factor: 0.639

3.  Machine learning methods can more efficiently predict prostate cancer compared with prostate-specific antigen density and prostate-specific antigen velocity.

Authors:  Satoshi Nitta; Masakazu Tsutsumi; Shotaro Sakka; Tsuyoshi Endo; Kenichiro Hashimoto; Morikuni Hasegawa; Takayuki Hayashi; Koji Kawai; Hiroyuki Nishiyama
Journal:  Prostate Int       Date:  2019-01-29

4.  Artificial neural network (ANN) velocity better identifies benign prostatic hyperplasia but not prostate cancer compared with PSA velocity.

Authors:  Carsten Stephan; Nicola Büker; Henning Cammann; Hellmuth-Alexander Meyer; Michael Lein; Klaus Jung
Journal:  BMC Urol       Date:  2008-09-02       Impact factor: 2.264

  4 in total

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