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

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Assay-specific artificial neural networks for five different PSA assays and populations with PSA 2-10 ng/ml in 4,480 men. / Stephan, Carsten; Xu, Chuanliang; Cammann, Henning; Graefen, Markus; Haese, Alexander; Huland, Hartwig; Semjonow, Axel; Diamandis, Eleftherios P; Remzi, Mesut; Djavan, Bob; Wildhagen, Mark F; Blijenberg, Bert G; Finne, Patrik; Stenman, Ulf-Hakan; Jung, Klaus; Meyer, Hellmuth-Alexander.

In: WORLD J UROL, Vol. 25, No. 1, 1, 2007, p. 95-103.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Stephan, C, Xu, C, Cammann, H, Graefen, M, Haese, A, Huland, H, Semjonow, A, Diamandis, EP, Remzi, M, Djavan, B, Wildhagen, MF, Blijenberg, BG, Finne, P, Stenman, U-H, Jung, K & Meyer, H-A 2007, '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, vol. 25, no. 1, 1, pp. 95-103. <http://www.ncbi.nlm.nih.gov/pubmed/17333205?dopt=Citation>

APA

Stephan, C., Xu, C., Cammann, H., Graefen, M., Haese, A., Huland, H., Semjonow, A., Diamandis, E. P., Remzi, M., Djavan, B., Wildhagen, M. F., Blijenberg, B. G., Finne, P., Stenman, U-H., Jung, K., & Meyer, H-A. (2007). 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, 25(1), 95-103. [1]. http://www.ncbi.nlm.nih.gov/pubmed/17333205?dopt=Citation

Vancouver

Stephan C, Xu C, Cammann H, Graefen M, Haese A, Huland H et al. 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;25(1):95-103. 1.

Bibtex

@article{1beada3112c54161ad00b3013b76acd2,
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.",
author = "Carsten Stephan and Chuanliang Xu and Henning Cammann and Markus Graefen and Alexander Haese and Hartwig Huland and Axel Semjonow and Diamandis, {Eleftherios P} and Mesut Remzi and Bob Djavan and Wildhagen, {Mark F} and Blijenberg, {Bert G} and Patrik Finne and Ulf-Hakan Stenman and Klaus Jung and Hellmuth-Alexander Meyer",
year = "2007",
language = "Deutsch",
volume = "25",
pages = "95--103",
journal = "WORLD J UROL",
issn = "0724-4983",
publisher = "Springer",
number = "1",

}

RIS

TY - JOUR

T1 - Assay-specific artificial neural networks for five different PSA assays and populations with PSA 2-10 ng/ml in 4,480 men.

AU - Stephan, Carsten

AU - Xu, Chuanliang

AU - Cammann, Henning

AU - Graefen, Markus

AU - Haese, Alexander

AU - Huland, Hartwig

AU - Semjonow, Axel

AU - Diamandis, Eleftherios P

AU - Remzi, Mesut

AU - Djavan, Bob

AU - Wildhagen, Mark F

AU - Blijenberg, Bert G

AU - Finne, Patrik

AU - Stenman, Ulf-Hakan

AU - Jung, Klaus

AU - Meyer, Hellmuth-Alexander

PY - 2007

Y1 - 2007

N2 - 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.

AB - 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.

M3 - SCORING: Zeitschriftenaufsatz

VL - 25

SP - 95

EP - 103

JO - WORLD J UROL

JF - WORLD J UROL

SN - 0724-4983

IS - 1

M1 - 1

ER -