Literature DB >> 21705045

Development of improved nomogram for prediction of outcome of initial prostate biopsy using readily available clinical information.

Osama M Zaytoun1, Michael W Kattan, Ayman S Moussa, Jianbo Li, Changhong Yu, J Stephen Jones.   

Abstract

OBJECTIVES: To construct a nomogram that can be used to estimate the risk of prostate cancer (PCa) and high-grade PCa using readily available clinical information for men undergoing initial extended prostate biopsy (PBx). Many nomograms have been developed to predict the outcome of initial PBx. However, most require information not available at the decision to biopsy.
METHODS: From March 2000 to April 2010, 1551 men with a prostate-specific antigen (PSA) of ≤10 ng/mL who underwent initial extended PBx were included in the present study. The nomogram predictor variables were patient age, race, prostate-specific antigen (PSA) level, percent free PSA, family history of PCa, and the digital rectal examination findings. The area under the receiver operating characteristic curve was calculated as a measure of discrimination. The calibration was assessed graphically.
RESULTS: Of the 1551 men, 606 (39.1%) had PCa on biopsy. The mean value for age, PSA, and percent free PSA was 63.4 years, 5.1 ng/mL, and 21.4%, respectively. Also, 25.1% and 7.8% of patients with positive PBx findings had digital rectal examination abnormalities and a positive family history, respectively. The univariate and multivariate analyses suggested that all 6 risk factors were predictors of PCa in the study cohort (P < .05). The area under the curve for all factors in a model predicting PCa was 0.73 (95% confidence interval 0.71-0.76). The area under the curve for predicting high-grade PCa was 0.71 (95% confidence interval 0.69-0.74).
CONCLUSIONS: The present predictive model allows an assessment of the risk of PCa and high-grade PCa for men undergoing initial extended PBx using readily available, noninvasively obtained clinical data.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21705045     DOI: 10.1016/j.urology.2011.04.042

Source DB:  PubMed          Journal:  Urology        ISSN: 0090-4295            Impact factor:   2.649


  10 in total

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2.  Development and validation of a nomogram for predicting prostate cancer in men with prostate-specific antigen grey zone based on retrospective analysis of clinical and multi-parameter magnetic resonance imaging/transrectal ultrasound fusion-derived data.

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3.  Integration of magnetic resonance imaging into prostate cancer nomograms.

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4.  Testing for the recurrent HOXB13 G84E germline mutation in men with clinical indications for prostate biopsy.

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Review 5.  The role of biomarkers in the assessment of prostate cancer risk prior to prostate biopsy: which markers matter and how should they be used?

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6.  Nomogram for prediction of prostate cancer with serum prostate specific antigen less than 10 ng/mL.

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7.  Development and validation of a nomogram for predicting prostate cancer in patients with PSA ≤ 20 ng/mL at initial biopsy.

Authors:  Qiang Wu; Fanglong Li; Xiaotao Yin; Jiangping Gao; Xu Zhang
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8.  Outcomes and trends of prostate biopsy for prostate cancer in Chinese men from 2003 to 2011.

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9.  Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy.

Authors:  Jose Rubio-Briones; Angel Borque; Luis M Esteban; Juan Casanova; Antonio Fernandez-Serra; Luis Rubio; Irene Casanova-Salas; Gerardo Sanz; Jose Domínguez-Escrig; Argimiro Collado; Alvaro Gómez-Ferrer; Inmaculada Iborra; Miguel Ramírez-Backhaus; Francisco Martínez; Ana Calatrava; Jose A Lopez-Guerrero
Journal:  BMC Cancer       Date:  2015-09-11       Impact factor: 4.430

10.  Prevalence and Risk Factors of Prostate Cancer in Chinese Men with PSA 4-10 ng/mL Who Underwent TRUS-Guided Prostate Biopsy: The Utilization of PAMD Score.

Authors:  Dong Fang; Da Ren; Chenglin Zhao; Xuesong Li; Wei Yu; Rui Wang; Huihui Wang; Chenguang Xi; Qun He; Xiaoying Wang; Zhongcheng Xin; Liqun Zhou
Journal:  Biomed Res Int       Date:  2015-10-18       Impact factor: 3.411

  10 in total

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