Assay-specific artificial neural networks for five different PSA assays and populations with PSA 2-10 ng/ml in 4,480 men

World J Urol. 2007 Mar;25(1):95-103. doi: 10.1007/s00345-006-0132-9. Epub 2007 Feb 28.

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.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Biomarkers, Tumor / blood
  • Humans
  • Male
  • Mass Screening / instrumentation*
  • Mass Screening / methods
  • Middle Aged
  • Neural Networks, Computer*
  • Prostate-Specific Antigen / blood*
  • Prostatic Neoplasms / blood*
  • Prostatic Neoplasms / diagnosis*
  • Prostatic Neoplasms / epidemiology
  • ROC Curve
  • Risk Factors
  • Sensitivity and Specificity

Substances

  • Biomarkers, Tumor
  • Prostate-Specific Antigen