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
✍ Scribed by 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
- Publisher
- John Wiley and Sons
- Year
- 2002
- Tongue
- French
- Weight
- 221 KB
- Volume
- 99
- Category
- Article
- ISSN
- 0020-7136
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✦ Synopsis
Abstract
Our study was performed to evaluate the diagnostic usefulness of %fPSA alone and combined with an ANN at different PSA concentration ranges, including the low range 2–4 ng/ml, to improve the risk assessment of prostate cancer. A total of 928 men with prostate cancer and BPH without any pretreatment of the prostate in the PSA range 2–20 ng/ml were enrolled in the study between 1996 and 2001. An ANN with input data of PSA, %fPSA, patient's age, prostate volume and DRE status was developed to calculate the individual's risk before performing a prostate biopsy within the different PSA ranges 2–4, 4.1–10 and 10.1–20 ng/ml. ROC analysis and cut‐off calculations were used to estimate the diagnostic improvement of %fPSA and ANN in comparison to PSA. At the 90% sensitivity level, %fPSA and ANN performed better than PSA in all ranges, enhancing the specificity by 15–28% and 32–44%, respectively. For the low PSA range 2–4 ng/mL, we recommend a first‐time biopsy at an ANN specificity level of 90%. For PSA 4–10 ng/mL, we recommend a first‐time biopsy based on the ANN at the 90% sensitivity level. Use of an ANN enhances the %fPSA performance to further reduce the number of unnecessary biopsies within the PSA range 2–10 ng/ml. © 2002 Wiley‐Liss, Inc.