title: Assay-specific artificial neural networks for five different PSA assays and populations with PSA 2-10 ng/ml in 4,480 men.
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.
authors.affiliation: Department of Urology, Charité-Universitätsmedizin Berlin, CCM, Berlin, Germany. carsten.stephan@charite.de
authors.forename: Carsten
authors.initials: C
authors.lastname: Stephan
authors.forename: Chuanliang
authors.initials: C
authors.lastname: Xu
authors.forename: Henning
authors.initials: H
authors.lastname: Cammann
authors.forename: Markus
authors.initials: M
authors.lastname: Graefen
authors.forename: Alexander
authors.initials: A
authors.lastname: Haese
authors.forename: Hartwig
authors.initials: H
authors.lastname: Huland
authors.forename: Axel
authors.initials: A
authors.lastname: Semjonow
authors.forename: Eleftherios P
authors.initials: EP
authors.lastname: Diamandis
authors.forename: Mesut
authors.initials: M
authors.lastname: Remzi
authors.forename: Bob
authors.initials: B
authors.lastname: Djavan
authors.forename: Mark F
authors.initials: MF
authors.lastname: Wildhagen
authors.forename: Bert G
authors.initials: BG
authors.lastname: Blijenberg
authors.forename: Patrik
authors.initials: P
authors.lastname: Finne
authors.forename: Ulf-Hakan
authors.initials: UH
authors.lastname: Stenman
authors.forename: Klaus
authors.initials: K
authors.lastname: Jung
authors.forename: Hellmuth-Alexander
authors.initials: HA
authors.lastname: Meyer
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000097:blood; D006801:Humans; D008297:Male; D008403:Mass Screening / Q000295:instrumentation* / Q000379:methods; D008875:Middle Aged; D016571:Neural Networks, Computer; D017430:Prostate-Specific Antigen / Q000097:blood*; D011471:Prostatic Neoplasms / Q000097:blood* / Q000175:diagnosis* / Q000453:epidemiology; D012372:ROC Curve; D012307:Risk Factors; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor; D017430:Prostate-Specific Antigen