Initial biopsy outcome prediction--head-to-head comparison of a logistic regression-based nomogram versus artificial neural network.
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Initial biopsy outcome prediction--head-to-head comparison of a logistic regression-based nomogram versus artificial neural network. / Chun, Felix; Graefen, Markus; Briganti, Alberto; Gallina, Andrea; Hopp, Julia; Kattan, Michael W; Huland, Hartwig; Karakiewicz, Pierre I.
in: EUR UROL, Jahrgang 51, Nr. 5, 5, 2007, S. 1233-1236.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - Initial biopsy outcome prediction--head-to-head comparison of a logistic regression-based nomogram versus artificial neural network.
AU - Chun, Felix
AU - Graefen, Markus
AU - Briganti, Alberto
AU - Gallina, Andrea
AU - Hopp, Julia
AU - Kattan, Michael W
AU - Huland, Hartwig
AU - Karakiewicz, Pierre I
PY - 2007
Y1 - 2007
N2 - OBJECTIVES: Nomograms and artificial neural networks (ANNs) represent alternative methodologic approaches to predict the probability of prostate cancer on initial biopsy. We hypothesized that, in a head-to-head comparison, one of the approaches might demonstrate better accuracy and performance characteristics than the other. METHODS: A previously published nomogram, which relies on age, digital rectal examination, serum prostate-specific antigen (PSA), and percent-free PSA, and an ANN, which relies on the same predictors plus prostate volume, were applied to a cohort of 3980 men, who were subjected to multicore systematic prostate biopsy. The accuracy and the performance characteristics were compared between these two approaches. RESULTS: The accuracy of the nomogram was 71% versus 67% for the ANN (p=0.0001). Graphical exploration of the performance characteristics demonstrated virtually perfect predictions for the nomogram. Conversely, the ANN underestimated the observed rate of prostate cancer. CONCLUSIONS: A 4% increase in predictive accuracy implies that the use of the nomogram instead of the ANN will result in 40 additional patients who will be correctly classified between benign and cancer.
AB - OBJECTIVES: Nomograms and artificial neural networks (ANNs) represent alternative methodologic approaches to predict the probability of prostate cancer on initial biopsy. We hypothesized that, in a head-to-head comparison, one of the approaches might demonstrate better accuracy and performance characteristics than the other. METHODS: A previously published nomogram, which relies on age, digital rectal examination, serum prostate-specific antigen (PSA), and percent-free PSA, and an ANN, which relies on the same predictors plus prostate volume, were applied to a cohort of 3980 men, who were subjected to multicore systematic prostate biopsy. The accuracy and the performance characteristics were compared between these two approaches. RESULTS: The accuracy of the nomogram was 71% versus 67% for the ANN (p=0.0001). Graphical exploration of the performance characteristics demonstrated virtually perfect predictions for the nomogram. Conversely, the ANN underestimated the observed rate of prostate cancer. CONCLUSIONS: A 4% increase in predictive accuracy implies that the use of the nomogram instead of the ANN will result in 40 additional patients who will be correctly classified between benign and cancer.
M3 - SCORING: Zeitschriftenaufsatz
VL - 51
SP - 1233
EP - 1236
JO - EUR UROL
JF - EUR UROL
SN - 0302-2838
IS - 5
M1 - 5
ER -
