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Multicenter Evaluation of an Artificial Neural Network to Increase the Prostate Cancer Detection Rate and Reduce Unnecessary Biopsies by Carsten Stephan; Henning Cammann; Axel Semjonow; Eleftherios P Diamandis; Leon FA Wymenga; Michael Lein; Pranav Sinha; Stefan A Loening; Klaus Jung is a Medicine article available to read on EtoBox.

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## 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 microg/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 microg/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 microg/l), the ann detected 72% and 65% of cancers at specificities of 90% or 95%, respectively. at 4-10 microg/l tpsa, the ann detected

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Author

Carsten Stephan; Henning Cammann; Axel Semjonow; Eleftherios P Diamandis; Leon FA Wymenga; Michael Lein; Pranav Sinha; Stefan A Loening; Klaus Jung

Publisher

Oxford University Press (OUP)

Published

2002

Language

EN

Field

Medicine (Health Sciences)