Literature DB >> 29155186

Prediction of Prostate Cancer Risk Among Men Undergoing Combined MRI-targeted and Systematic Biopsy Using Novel Pre-biopsy Nomograms That Incorporate MRI Findings.

Marc A Bjurlin1, Andrew B Rosenkrantz2, Saradwata Sarkar3, Herbert Lepor1, William C Huang1, Richard Huang1, Rajesh Venkataraman3, Samir S Taneja4.   

Abstract

OBJECTIVE: To develop nomograms that predict the probability of overall prostate cancer (PCa) and clinically significant PCa (Gleason ≥7) on magnetic resonance imaging (MRI)-targeted, and combined MRI-targeted and systematic, prostate biopsy.
MATERIALS AND METHODS: From June 2012 to August 2014, magnetic resonance imaging to ultrasound fusion-targeted prostate biopsy was performed on 464 men with suspicious regions identified on pre-biopsy 3T MRI along with systematic 12 core biopsy. Logistic regression modeling was used to evaluate predictors of overall and clinically significant PCa, and corresponding nomograms were generated for men who were not previously biopsied or had 1 or more prior negative biopsies. Models were created with 70% of a randomly selected training sample and bias-corrected using bootstrap resampling. The models were then validated with the remaining 30% testing sample pool.
RESULTS: A total of 459 patients were included for analysis (median age 66 years, prostate-specific antigen [PSA] 5.2 ng/mL, prostate volume 49 cc). Independent predictors of PCa on targeted and systematic prostate biopsy were PSA density, age, and MRI suspicion score. PCa probability nomograms were generated for each cohort using the predictors. Bias-corrected areas under the receiver-operating characteristic curves for overall and clinically significant PCa detection were 0.82 (0.78) and 0.91 (0.84) for men without prior biopsy and 0.76 (0.65) and 0.86 (0.87) for men with a prior negative biopsy in the training (testing) samples.
CONCLUSION: PSA density, age, and MRI suspicion score predict PCa on combined MRI-targeted and systematic biopsy. Our generated nomograms demonstrate high diagnostic accuracy and may further aid in the decision to perform biopsy in men with clinical suspicion of PCa.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 29155186     DOI: 10.1016/j.urology.2017.09.035

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


  12 in total

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Journal:  Can Urol Assoc J       Date:  2018-10-15       Impact factor: 1.862

Review 2.  PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway.

Authors:  Anwar R Padhani; Jelle Barentsz; Geert Villeirs; Andrew B Rosenkrantz; Daniel J Margolis; Baris Turkbey; Harriet C Thoeny; François Cornud; Masoom A Haider; Katarzyna J Macura; Clare M Tempany; Sadhna Verma; Jeffrey C Weinreb
Journal:  Radiology       Date:  2019-06-11       Impact factor: 11.105

Review 3.  Follow-up of negative MRI-targeted prostate biopsies: when are we missing cancer?

Authors:  Samuel A Gold; Graham R Hale; Jonathan B Bloom; Clayton P Smith; Kareem N Rayn; Vladimir Valera; Bradford J Wood; Peter L Choyke; Baris Turkbey; Peter A Pinto
Journal:  World J Urol       Date:  2018-05-21       Impact factor: 4.226

4.  How Would MRI-targeted Prostate Biopsy Alter Radiation Therapy Approaches in Treating Prostate Cancer?

Authors:  Daniel B Dix; Andrew M McDonald; Jennifer B Gordetsky; Jeffrey W Nix; John V Thomas; Soroush Rais-Bahrami
Journal:  Urology       Date:  2018-08-30       Impact factor: 2.649

5.  Comparative Analysis of PSA Density and an MRI-Based Predictive Model to Improve the Selection of Candidates for Prostate Biopsy.

Authors:  Juan Morote; Angel Borque-Fernando; Marina Triquell; Anna Celma; Lucas Regis; Richard Mast; Inés M de Torres; María E Semidey; José M Abascal; Pol Servian; Anna Santamaría; Jacques Planas; Luis M Esteban; Enrique Trilla
Journal:  Cancers (Basel)       Date:  2022-05-11       Impact factor: 6.575

6.  Prostate Imaging-Reporting and Data System Steering Committee: PI-RADS v2 Status Update and Future Directions.

Authors:  Anwar R Padhani; Jeffrey Weinreb; Andrew B Rosenkrantz; Geert Villeirs; Baris Turkbey; Jelle Barentsz
Journal:  Eur Urol       Date:  2018-06-13       Impact factor: 20.096

7.  How to implement magnetic resonance imaging before prostate biopsy in clinical practice: nomograms for saving biopsies.

Authors:  Ángel Borque-Fernando; Luis Mariano Esteban; Ana Celma; Sarai Roche; Jacques Planas; Lucas Regis; Inés de Torres; Maria Eugenia Semidey; Enrique Trilla; Juan Morote
Journal:  World J Urol       Date:  2019-09-10       Impact factor: 4.226

Review 8.  Multivariate risk prediction tools including MRI for individualized biopsy decision in prostate cancer diagnosis: current status and future directions.

Authors:  Ivo G Schoots; Monique J Roobol
Journal:  World J Urol       Date:  2019-03-13       Impact factor: 4.226

9.  Evaluation of MSKCC Preprostatectomy nomogram in men who undergo MRI-targeted prostate biopsy prior to radical prostatectomy.

Authors:  Zachary A Glaser; Jennifer B Gordetsky; Sejong Bae; Jeffrey W Nix; Kristin K Porter; Soroush Rais-Bahrami
Journal:  Urol Oncol       Date:  2019-09-05       Impact factor: 3.498

10.  The Barcelona Predictive Model of Clinically Significant Prostate Cancer.

Authors:  Juan Morote; Angel Borque-Fernando; Marina Triquell; Anna Celma; Lucas Regis; Manel Escobar; Richard Mast; Inés M de Torres; María E Semidey; José M Abascal; Carles Sola; Pol Servian; Daniel Salvador; Anna Santamaría; Jacques Planas; Luis M Esteban; Enrique Trilla
Journal:  Cancers (Basel)       Date:  2022-03-21       Impact factor: 6.639

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