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Volume 2012 (2012), Article ID 643181, 6 pages
External Validation of an Artificial Neural Network and Two Nomograms for Prostate Cancer Detection
1Department of Urology, HELIOS Hospital, 15526 Bad Saarow, Germany
2Institute of Pathology, HELIOS Hospital, Bad Saarow, Germany
3Institute of Medical Informatics, Charité—Universitätsmedizin Berlin, 10098 Berlin, Germany
4Department of Urology, Lukas Hospital Neuss, Germany
5Department of Urology, Charité—Universitätsmedizin Berlin, 10098 Berlin, Germany
Received 9 April 2012; Accepted 13 May 2012
Academic Editors: P.-L. Chang, J. H. Ku, and T. Okamura
Copyright © 2012 Thorsten H. Ecke et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- H. Lilja, D. Ulmert, and A. J. Vickers, “Prostate-specific antigen and prostate cancer: prediction, detection and monitoring,” Nature Reviews Cancer, vol. 8, no. 4, pp. 268–278, 2008.
- F. H. Schröder, P. van der Maas, P. Beemsterboer et al., “Evaluation of the digital rectal examination as a screening test for prostate cancer,” Journal of the National Cancer Institute, vol. 90, no. 23, pp. 1817–1823, 1998.
- C. K. Naughton, D. S. Smith, P. A. Humphrey, W. J. Catalona, and D. W. Keetch, “Clinical and pathologic tumor characteristics of prostate cancer as a function of the number of biopsy cores: a retrospective study,” Journal of Urology, vol. 52, no. 5, pp. 808–813, 1998.
- T. J. Polascik, J. E. Oesterling, and A. W. Partin, “Prostate specific antigen: a decade of discovery—what we have learned and where we are going,” Journal of Urology, vol. 162, no. 2, pp. 293–306, 1999.
- C. T. Lee and P. T. Scardino, “Percent free prostate-specific antigen for first-time prostate biopsy.,” Journal of Urology, vol. 57, no. 4, pp. 594–598, 2001.
- C. Stephan, M. Lein, K. Jung, D. Schnorr, and S. A. Loening, “Re: editorial: can prostate specific antigen derivatives reduce the frequency of unnecessary prostate biopsies?” The Journal of Urology, vol. 157, no. 4, article 1371, 1997.
- M. Garzotto, R. G. Hudson, L. Peters et al., “Predictive modeling for the presence of prostate carcinoma using clinical, laboratory, and ultrasound parameters in patients with prostate specific antigen levels ≤ 10 ng/mL,” Cancer, vol. 98, no. 7, pp. 1417–1422, 2003.
- P. I. Karakiewicz, S. Benayoun, M. W. Kattan et al., “Development and validation of a nomogram predicting the outcome of prostate biopsy based on patient age, digital rectal examination and serum prostate specific antigen,” Journal of Urology, vol. 173, no. 6, pp. 1930–1934, 2005.
- J. A. Eastham, R. May, J. L. Robertson, O. Sartor, and M. W. Kattan, “Development of a nomogram that predicts the probability of a positive prostate biopsy in men with an abnormal digital rectal examination and a prostate-specific antigen between 0 and 4 ng/mL,” Journal of Urology, vol. 54, no. 4, pp. 709–713, 1999.
- C. Stephan, H. Cammann, A. Semjonow et al., “Multicenter evaluation of an artificial neural network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clinical Chemistry, vol. 48, no. 8, pp. 1279–1287, 2002.
- P. Finne, R. Finne, A. Auvinen et al., “Predicting the outcome of prostate biopsy in screen-positive men by a multilayer perceptron network,” Journal of Urology, vol. 56, no. 3, pp. 418–422, 2000.
- R. J. Babaian, H. Fritsche, A. Ayala et al., “Performance of a neural network in detecting prostate cancer in the prostate-specific antigen reflex range of 2.5 to 4.0 ng/mL,” Journal of Urology, vol. 56, no. 6, pp. 1000–1006, 2000.
- F. K. H. Chun, P. I. Karakiewicz, A. Briganti et al., “A critical appraisal of logistic regression-based nomograms, artificial neural networks, classification and regression-tree models, look-up tables and risk-group stratification models for prostate cancer,” BJU International, vol. 99, no. 4, pp. 794–800, 2007.
- F. Schröder and M. W. Kattan, “The comparability of models for predicting the risk of a positive prostate biopsy with prostate-specific antigen alone: a systematic review,” European Urology, vol. 54, no. 2, pp. 274–290, 2008.
- C. Stephan, H. Cammann, H. A. Meyer, M. Lein, and K. Jung, “PSA and new biomarkers within multivariate models to improve early detection of prostate cancer,” Cancer Letters, vol. 249, no. 1, pp. 18–29, 2007.
- F. K. H. Chun, M. Graefen, A. Briganti et al., “Initial biopsy outcome prediction-head-to-head comparison of a logistic regression-based nomogram versus artificial neural network,” European Urology, vol. 51, no. 5, pp. 1236–1243, 2007.
- C. Stephan, H.-A. Meyer, H. Cammann, M. Lein, S. A. Loening, and K. Jung, “Re: Felix K.-H. Chun, Markus Graefen, Alberto Briganti, Andrea Gallina, Julia Hopp, Michael W. Kattan, Hartwig Huland and Pierre I. Karakiewicz. Initial biopsy outcome prediction-head-to-head comparison of a logistic regression-based nomogram versus artificial neural network. Eur Urol 2007; 51: 1236-43,” European Urology, vol. 51, no. 5, pp. 1446–1447, 2007.
- S. Kawakami, N. Numao, Y. Okubo et al., “Development, validation, and head-to-head comparison of logistic regression-based nomograms and artificial neural network models predicting prostate cancer on initial extended biopsy,” European Urology, vol. 54, no. 3, pp. 601–611, 2008.
- C. Stephan, H. Cammann, H. A. Meyer et al., “An artificial neural network for five different assay systems of prostate-specific antigen in prostate cancer diagnostics,” BJU International, vol. 102, no. 7, pp. 799–805, 2008.
- T. Utsumi, K. Kawamura, H. Suzuki et al., “External validation and head-to-head comparison of japanese and Western prostate biopsy nomograms using japanese data sets,” International Journal of Urology, vol. 16, no. 4, pp. 416–419, 2009.
- W. Horninger, G. Bartsch, P. B. Snow, J. M. Brandt, and A. W. Partin, “The problem of cutoff levels in a screened population: appropriateness of informing screenees about their risk of having prostate carcinoma,” Cancer, vol. 91, no. 8, pp. 1667–1672, 2001.
- C. Stephan, K. Jung, H. Cammann et al., “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,” International Journal of Cancer, vol. 99, no. 3, pp. 466–473, 2002.
- F. Greene, D. Page, and I. Fleming, American Joint Committee on Cancer Staging Manual, Springer, New York, NY, USA, 2002.
- T. H. Ecke, S. Gunia, P. Bartel, S. Hallmann, S. Koch, and J. Ruttloff, “Complications and risk factors of transrectal ultrasound guided needle biopsies of the prostate evaluated by questionnaire,” Urologic Oncology, vol. 26, no. 5, pp. 474–478, 2008.
- V. Kairisto and A. Poola, “Software for illustrative presentation of basic clinical characteristics of laboratory tests—GraphROC for windows,” Scandinavian Journal of Clinical and Laboratory Investigation, vol. 55, supplement 222, pp. 43–60, 1995.
- W. J. Catalona, A. W. Partin, K. M. Slawin et al., “Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial,” Journal of the American Medical Association, vol. 279, no. 19, pp. 1542–1547, 1998.
- C. Stephan, C. Xu, P. Finne et al., “Comparison of two different artificial neural networks for prostate biopsy indication in two different patient populations,” Journal of Urology, vol. 70, no. 3, pp. 596–601, 2007.