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Departments of
1
Urology and
6 Laboratory Medicine and Pathobiochemistry, and
3 Institute for Medical Biometry, University Hospital Charité, Humboldt University, D-10098 Berlin, Germany.
2 Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, M5G 1X5 Canada.
4 Department of Urology, Westfälische Wilhelms-University, D-48129 Münster, Germany.
5 Department of Urology, Martini Hospital, NL-9700 Groningen, The Netherlands.
aAddress correspondence to this author at: Department of Urology, University Hospital Charité, Humboldt University Berlin, Schumannstrasse 20/21, D-10098 Berlin, Germany. Fax 49-30-450-515904; e-mail carsten.stephan{at}charite.de.
Background: The percentage of free prostate-specific antigen (%fPSA) has been shown to improve specificity for the diagnosis of prostate cancer (PCa) over total PSA (tPSA). A multicenter study was performed to evaluate the diagnostic value of a %fPSA-based artificial neural network (ANN) in men with tPSA concentrations between 2 and 20 µg/L for detecting patients with increased risk of a positive prostate biopsy for cancer.
Methods: We enrolled 1188 men from six different hospitals with PCa or benign prostates between 1996 and 2001. We used a newly developed ANN with input data of tPSA, %fPSA, patient age, prostate volume, and digital rectal examination (DRE) status to calculate the risk for the presence of PCa within different tPSA ranges (2–4, 4.1–10, 2–10, 10.1–20, and 2–20 µg/L) at the 90% and 95% specificity or sensitivity cutoffs, depending on the tPSA concentration. ROC analysis and cutoff calculations were used to estimate the diagnostic improvement of the ANN compared with %fPSA alone.
Results: In the low tPSA range (2–4 µg/L), the ANN detected 72% and 65% of cancers at specificities of 90% or 95%, respectively. At 4–10 µg/L tPSA, the ANN detected 90% and 95% of cancers with specificities of 62% and 41%, respectively. Use of the ANN with 2–10 µg/L tPSA enhanced the specificity of %fPSA by 20–22%, thus reducing the number of unnecessary biopsies.
Conclusions: Enhanced accuracy of PCa detection over that obtained using %fPSA alone can be achieved with a %fPSA-based ANN that also includes clinical information from DRE and prostate volume measurements.
The following articles in journals at HighWire Press have cited this article:
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  S. F. Shariat, P. I. Karakiewicz, N. Suardi, and M. W. Kattan Comparison of Nomograms With Other Methods for Predicting Outcomes in Prostate Cancer: A Critical Analysis of the Literature Clin. Cancer Res., July 15, 2008; 14(14): 4400 - 4407. [Abstract] [Full Text] [PDF]
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 D. B. P. Eekers, A. Laschet, M. de Groot, E. Roelofs, A. Kester, K. Delaere, P. Lambin, F. van Gils, M. Nap, and J. ten Kate Why determine only the total prostate-specific antigen, if the free-to-total ratio contains the information? Ann Clin Biochem, May 1, 2008; 45(3): 270 - 274. [Abstract] [Full Text] [PDF]
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L. Hu, J. L-S. Au, and M. G. Wientjes Computational Modeling to Predict Effect of Treatment Schedule on Drug Delivery to Prostate in Humans Clin. Cancer Res., February 15, 2007; 13(4): 1278 - 1287. [Abstract] [Full Text] [PDF]
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 H. J. Lee, K. G. Kim, S. E. Lee, S.-S. Byun, S. I. Hwang, S. I. Jung, S. K. Hong, and S. H. Kim Role of transrectal ultrasonography in the prediction of prostate cancer: artificial neural network analysis. J. Ultrasound Med., July 1, 2006; 25(7): 815 - 821. [Abstract] [Full Text] [PDF]
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D. A. Brown, C. Stephan, R. L. Ward, M. Law, M. Hunter, A. R. Bauskin, J. Amin, K. Jung, E. P. Diamandis, G. M. Hampton, et al. Measurement of Serum Levels of Macrophage Inhibitory Cytokine 1 Combined with Prostate-Specific Antigen Improves Prostate Cancer Diagnosis Clin. Cancer Res., January 1, 2006; 12(1): 89 - 96. [Abstract] [Full Text] [PDF]
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 M. Ollert, S. Weissenbacher, J. Rakoski, and J. Ring Allergen-Specific IgE Measured by a Continuous Random-Access Immunoanalyzer: Interassay Comparison and Agreement with Skin Testing Clin. Chem., July 1, 2005; 51(7): 1241 - 1249. [Abstract] [Full Text] [PDF]
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 Y. Matsui, N. Utsunomiya, K. Ichioka, N. Ueda, K. Yoshimura, A. Terai, and Y. Arai The Use of Artificial Neural Network Analysis to Improve the Predictive Accuracy of Prostate Biopsy in the Japanese Population Jpn. J. Clin. Oncol., October 1, 2004; 34(10): 602 - 607. [Abstract] [Full Text] [PDF]
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B. Lumbreras-Lacarra, J. M. Ramos-Rincon, and I. Hernandez-Aguado Methodology in Diagnostic Laboratory Test Research in Clinical Chemistry and Clinical Chemistry and Laboratory Medicine Clin. Chem., March 1, 2004; 50(3): 530 - 536. [Abstract] [Full Text] [PDF]
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 A. Michael, C. Stephan, D. Schnorr, S. A. Loening, and K. Jung Serum Macrophage Migration Inhibitory Factor Is Not Elevated in Patients with Prostate Cancer Cancer Epidemiol. Biomarkers Prev., February 1, 2004; 13(2): 328 - 329. [Full Text] [PDF]
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