Literature DB >> 22854248

Initial prostate biopsy: development and internal validation of a biopsy-specific nomogram based on the prostate cancer antigen 3 assay.

Jens Hansen1, Marco Auprich, Sascha A Ahyai, Alexandre de la Taille, Hendrik van Poppel, Michael Marberger, Arnulf Stenzl, Peter F A Mulders, Hartwig Huland, Margit Fisch, Clement-Claude Abbou, Jack A Schalken, Yves Fradet, Leonard S Marks, William Ellis, Alan W Partin, Karl Pummer, Markus Graefen, Alexander Haese, Jochen Walz, Alberto Briganti, Shahrokh F Shariat, Felix K Chun.   

Abstract

BACKGROUND: Urinary prostate cancer antigen 3 (PCA3) assay in combination with established clinical risk factors improves the identification of men at risk of harboring prostate cancer (PCa) at initial biopsy (IBX).
OBJECTIVE: To develop and validate internally the first IBX-specific PCA3-based nomogram that allows an individual assessment of a man's risk of harboring any PCa and high-grade PCa (HGPCa). DESIGN, SETTING, AND PARTICIPANTS: Clinical and biopsy data including urinary PCA3 score of 692 referred IBX men at risk of PCa were collected within two prospective multi-institutional studies. INTERVENTION: IBX (≥ 10 biopsy cores) with standard risk factor assessment including prebiopsy urinary PCA3 measurement. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: PCA3 assay cut-off thresholds were investigated. Regression coefficients of logistic risk factor analyses were used to construct specific sets of PCA3-based nomograms to predict any PCa and HGPCa at IBX. Accuracy estimates for the presence of any PCa and HGPCa were quantified using area under the curve of the receiver operator characteristic analysis and compared with a clinical model. Bootstrap resamples were used for internal validation. Decision curve analyses quantified the clinical net benefit related to the novel PCA3-based IBX nomogram versus the clinical model. RESULTS AND LIMITATIONS: Any PCa and HGPCa were diagnosed in 46% (n=318) and 20% (n=137), respectively. Age, prostate-specific antigen, digital rectal examination, prostate volume, and PCA3 were independent predictors of PCa at IBX (all p<0.001). The PCA3-based IBX nomograms significantly outperformed the clinical models without PCA3 (all p<0.001). Accuracy was increased by 4.5-7.1% related to PCA3 inclusion. When applying nomogram-derived PCa probability thresholds ≤ 30%, only a few patients with HGPCa (≤ 2%) will be missed while avoiding up to 55% of unnecessary biopsies. External validation of the PCA3-based IBX-specific nomogram is warranted.
CONCLUSIONS: The internally validated PCA3-based IBX-specific nomogram outperforms a clinical prediction model without PCA3 for the prediction of any PCa, leading to the avoidance of unnecessary biopsies while missing only a few cases of HGPCa. Our findings support the concepts of a combination of novel markers with established clinical risk factors and the superiority of decision tools that are specific to a clinical scenario.
Copyright © 2012 European Association of Urology. Published by Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22854248     DOI: 10.1016/j.eururo.2012.07.030

Source DB:  PubMed          Journal:  Eur Urol        ISSN: 0302-2838            Impact factor:   20.096


  39 in total

1.  Prediction of prostate cancer by deep learning with multilayer artificial neural network.

Authors:  Takumi Takeuchi; Mami Hattori-Kato; Yumiko Okuno; Satoshi Iwai; Koji Mikami
Journal:  Can Urol Assoc J       Date:  2018-10-15       Impact factor: 1.862

2.  Prostate-specific antigen screening in prostate cancer: perspectives on the evidence.

Authors:  Timothy J Wilt; Peter T Scardino; Sigrid V Carlsson; Ethan Basch
Journal:  J Natl Cancer Inst       Date:  2014-03-04       Impact factor: 13.506

3.  Additional value of PCA3 density to predict initial prostate biopsy outcome.

Authors:  A Ruffion; P Perrin; M Devonec; D Champetier; M Decaussin; P Paparel; V Vlaeminck-Guillem
Journal:  World J Urol       Date:  2014-02-06       Impact factor: 4.226

Review 4.  The role of prostate cancer biomarkers in undiagnosed men.

Authors:  Hasan Dani; Stacy Loeb
Journal:  Curr Opin Urol       Date:  2017-05       Impact factor: 2.309

5.  How to make clinical decisions to avoid unnecessary prostate screening in biopsy-naïve men with PI-RADs v2 score ≤ 3?

Authors:  Yu Zhang; Na Zeng; FengBo Zhang; YangXinRui Huang; Ye Tian
Journal:  Int J Clin Oncol       Date:  2019-08-31       Impact factor: 3.402

Review 6.  Urinary biomarkers for prostate cancer.

Authors:  John T Wei
Journal:  Curr Opin Urol       Date:  2015-01       Impact factor: 2.309

7.  Prostate transitional zone volume-based nomogram for predicting prostate cancer and high progression prostate cancer in a real-world population.

Authors:  Yanqing Wang; Shaowei Xie; Xun Shangguan; Jiahua Pan; Yinjie Zhu; Zhixiang Xin; Fan Xu; Xiaoguang Shao; Liancheng Fan; Jianjun Sha; Qiang Liu; Baijun Dong; Wei Xue
Journal:  J Cancer Res Clin Oncol       Date:  2017-03-10       Impact factor: 4.553

Review 8.  Function of PCA3 in prostate tissue and clinical research progress on developing a PCA3 score.

Authors:  Yue Wang; Xiao-Jun Liu; Xu-Dong Yao
Journal:  Chin J Cancer Res       Date:  2014-08       Impact factor: 5.087

Review 9.  RNA biomarkers to facilitate the identification of aggressive prostate cancer.

Authors:  Kathryn L Pellegrini; Martin G Sanda; Carlos S Moreno
Journal:  Mol Aspects Med       Date:  2015-05-27

10.  Assays for prostate cancer : changing the screening paradigm?

Authors:  Jens Hansen; Michael Rink; Markus Graefen; Shahrokh Shariat; Felix K-H Chun
Journal:  Mol Diagn Ther       Date:  2013-02       Impact factor: 4.074

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