External validation of Chun, PCPT, ERSPC, Kawakami, and Karakiewicz nomograms in the prediction of prostate cancer: A single center cohort-study

C De Nunzio, R Lombardo, G Tema, H Alkhatatbeh, G Gandaglia, A Briganti, A Tubaro

Research output: Contribution to journalArticle

Abstract

Objectives: The aim of our study was to analyze the performance of 5 different risk calculators for prostate cancer diagnosis: Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC), European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSP-RC), Karakiewicz nomogram, Chun nomogram, and Kawakami Nomogram. Methods: From 2008 onwards, we consecutively enrolled, at a single institution in Italy, men undergoing 12-core transrectal ultrasound-guided prostate needle biopsy. Demographic, clinical, and pathological data were collected. The risk of prostate cancer (PCa) was calculated according to the PCPT-RC, ERSPC-RC, Karakiewicz, Kawakami, and Chun nomograms. Calibration and discrimination were assessed using calibration plots and receiver operator characteristic analysis. Additionally, decision curve analyses (DCA) were used to assess the net benefit associated with the adoption of each model. Results: Overall, 1,100 patients were evaluated, 39% presented PCa and out of them 26% presented high-grade PCa (defined as Gleason ≥ 4 + 3). All the models showed good discrimination capacities for PCa on receiver operator characteristic analysis (area under the curve: 0.59–0.72) On calibration curves the ERSCP, the PCPT and the Chun nomogram underestimated the risk of PC while the Kawakami overestimated it. At DCA, the net benefit associated with the use of the models in the prediction of cancer was observed when the threshold probability was between 40% and 60%. Conclusion: In a cohort of Italian men undergoing prostate biopsy, the performance accuracy of these calculators for the prediction prostate cancer is suboptimal. According to our experience the use of these calculator in clinical practice should be encouraged. Although integration with new serum/urine markers or magnetic resonance imaging results is warranted. © 2018 Elsevier Inc.
Original languageEnglish
Pages (from-to)364.e1–364.e7
JournalUrologic Oncology: Seminars and Original Investigations
Volume36
Issue number8
DOIs
Publication statusPublished - 2018

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Nomograms
Prostatic Neoplasms
Cohort Studies
Calibration
Decision Support Techniques
Prostate
Needle Biopsy
Italy
Area Under Curve
Biomarkers
Magnetic Resonance Imaging
Demography
Urine
Biopsy

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External validation of Chun, PCPT, ERSPC, Kawakami, and Karakiewicz nomograms in the prediction of prostate cancer: A single center cohort-study. / De Nunzio, C; Lombardo, R; Tema, G; Alkhatatbeh, H; Gandaglia, G; Briganti, A; Tubaro, A.

In: Urologic Oncology: Seminars and Original Investigations, Vol. 36, No. 8, 2018, p. 364.e1–364.e7.

Research output: Contribution to journalArticle

@article{35fde1bde649413789d8e05d3ba3ea9d,
title = "External validation of Chun, PCPT, ERSPC, Kawakami, and Karakiewicz nomograms in the prediction of prostate cancer: A single center cohort-study",
abstract = "Objectives: The aim of our study was to analyze the performance of 5 different risk calculators for prostate cancer diagnosis: Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC), European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSP-RC), Karakiewicz nomogram, Chun nomogram, and Kawakami Nomogram. Methods: From 2008 onwards, we consecutively enrolled, at a single institution in Italy, men undergoing 12-core transrectal ultrasound-guided prostate needle biopsy. Demographic, clinical, and pathological data were collected. The risk of prostate cancer (PCa) was calculated according to the PCPT-RC, ERSPC-RC, Karakiewicz, Kawakami, and Chun nomograms. Calibration and discrimination were assessed using calibration plots and receiver operator characteristic analysis. Additionally, decision curve analyses (DCA) were used to assess the net benefit associated with the adoption of each model. Results: Overall, 1,100 patients were evaluated, 39{\%} presented PCa and out of them 26{\%} presented high-grade PCa (defined as Gleason ≥ 4 + 3). All the models showed good discrimination capacities for PCa on receiver operator characteristic analysis (area under the curve: 0.59–0.72) On calibration curves the ERSCP, the PCPT and the Chun nomogram underestimated the risk of PC while the Kawakami overestimated it. At DCA, the net benefit associated with the use of the models in the prediction of cancer was observed when the threshold probability was between 40{\%} and 60{\%}. Conclusion: In a cohort of Italian men undergoing prostate biopsy, the performance accuracy of these calculators for the prediction prostate cancer is suboptimal. According to our experience the use of these calculator in clinical practice should be encouraged. Although integration with new serum/urine markers or magnetic resonance imaging results is warranted. {\circledC} 2018 Elsevier Inc.",
author = "{De Nunzio}, C and R Lombardo and G Tema and H Alkhatatbeh and G Gandaglia and A Briganti and A Tubaro",
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T1 - External validation of Chun, PCPT, ERSPC, Kawakami, and Karakiewicz nomograms in the prediction of prostate cancer: A single center cohort-study

AU - De Nunzio, C

AU - Lombardo, R

AU - Tema, G

AU - Alkhatatbeh, H

AU - Gandaglia, G

AU - Briganti, A

AU - Tubaro, A

PY - 2018

Y1 - 2018

N2 - Objectives: The aim of our study was to analyze the performance of 5 different risk calculators for prostate cancer diagnosis: Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC), European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSP-RC), Karakiewicz nomogram, Chun nomogram, and Kawakami Nomogram. Methods: From 2008 onwards, we consecutively enrolled, at a single institution in Italy, men undergoing 12-core transrectal ultrasound-guided prostate needle biopsy. Demographic, clinical, and pathological data were collected. The risk of prostate cancer (PCa) was calculated according to the PCPT-RC, ERSPC-RC, Karakiewicz, Kawakami, and Chun nomograms. Calibration and discrimination were assessed using calibration plots and receiver operator characteristic analysis. Additionally, decision curve analyses (DCA) were used to assess the net benefit associated with the adoption of each model. Results: Overall, 1,100 patients were evaluated, 39% presented PCa and out of them 26% presented high-grade PCa (defined as Gleason ≥ 4 + 3). All the models showed good discrimination capacities for PCa on receiver operator characteristic analysis (area under the curve: 0.59–0.72) On calibration curves the ERSCP, the PCPT and the Chun nomogram underestimated the risk of PC while the Kawakami overestimated it. At DCA, the net benefit associated with the use of the models in the prediction of cancer was observed when the threshold probability was between 40% and 60%. Conclusion: In a cohort of Italian men undergoing prostate biopsy, the performance accuracy of these calculators for the prediction prostate cancer is suboptimal. According to our experience the use of these calculator in clinical practice should be encouraged. Although integration with new serum/urine markers or magnetic resonance imaging results is warranted. © 2018 Elsevier Inc.

AB - Objectives: The aim of our study was to analyze the performance of 5 different risk calculators for prostate cancer diagnosis: Prostate Cancer Prevention Trial Risk Calculator (PCPT-RC), European Randomized Study of Screening for Prostate Cancer Risk Calculator (ERSP-RC), Karakiewicz nomogram, Chun nomogram, and Kawakami Nomogram. Methods: From 2008 onwards, we consecutively enrolled, at a single institution in Italy, men undergoing 12-core transrectal ultrasound-guided prostate needle biopsy. Demographic, clinical, and pathological data were collected. The risk of prostate cancer (PCa) was calculated according to the PCPT-RC, ERSPC-RC, Karakiewicz, Kawakami, and Chun nomograms. Calibration and discrimination were assessed using calibration plots and receiver operator characteristic analysis. Additionally, decision curve analyses (DCA) were used to assess the net benefit associated with the adoption of each model. Results: Overall, 1,100 patients were evaluated, 39% presented PCa and out of them 26% presented high-grade PCa (defined as Gleason ≥ 4 + 3). All the models showed good discrimination capacities for PCa on receiver operator characteristic analysis (area under the curve: 0.59–0.72) On calibration curves the ERSCP, the PCPT and the Chun nomogram underestimated the risk of PC while the Kawakami overestimated it. At DCA, the net benefit associated with the use of the models in the prediction of cancer was observed when the threshold probability was between 40% and 60%. Conclusion: In a cohort of Italian men undergoing prostate biopsy, the performance accuracy of these calculators for the prediction prostate cancer is suboptimal. According to our experience the use of these calculator in clinical practice should be encouraged. Although integration with new serum/urine markers or magnetic resonance imaging results is warranted. © 2018 Elsevier Inc.

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DO - 10.1016/j.urolonc.2018.05.010

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SP - 364.e1–364.e7

JO - Urologic Oncology

JF - Urologic Oncology

SN - 1078-1439

IS - 8

ER -