Changes in prostate cancer detection rate of MRI-TRUS fusion vs systematic biopsy over time: Evidence of a learning curve

Document Type

Journal Article

Publication Date

12-1-2017

Journal

Prostate Cancer and Prostatic Diseases

Volume

20

Issue

4

DOI

10.1038/pcan.2017.34

Abstract

© 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Background:To determine the effect of urologist and radiologist learning curves and changes in MRI-TRUS fusion platform during 9 years of NCI's experience with multiparametric magnetic resonance imaging (mpMRI)/TRUS fusion biopsy.Methods:A prospectively maintained database of patients undergoing mpMRI followed by fusion biopsy (Fbx) and systematic biopsy (Sbx) from 2007 to 2016 was reviewed. The patients were stratified based on the timing of first biopsy. Cohort 1 (7/2007 d for learning curve. Cohort 2 (1/2011-5/2013) and cohort 3 (5/2013-4/2016) included patients biopsied prior to and after debut of a new software platform, respectively. Clinically significant (CS) disease was defined as Gleason 7 (3+4) or higher. McNemar's test compared cancer detection rates (CDRs) of Sbx and Fbx between time periods.Results:1528 patients were included in the study with 230, 537 and 761 patients included in three respective cohorts. Median age (interquartile range) was 61.0 (±9.0), 62.0 (±7.3), and 64.0 (±11.0) years in three cohorts, respectively (P<0.001). Fbx and Sbx had comparable CS CDR in cohort 1 (24.8 vs 22.2%, P=0.377). Fbx detected significantly more CS disease compared to Sbx in the following two periods (cohort 2: 31.5 vs 25.0%, P=0.001; cohort 3: 36.4 vs 30.3%, P<0.001) and detected significantly less low risk disease in the same period (cohort 2: 14.5 vs 19.6%, P<0.001; cohort 3: 12.6 vs 16.7%, P<0.001). Even after multivariate adjustment with age, PSA, race, clinical stage and MRI suspicion score, Fbx CS cancer detection increased in successive cohorts (cohort 2: OR 2.23, P=0.043; cohort 3: OR 2.92, P=0.007).Conclusions:In the past 9 years, there has been significant improvement in the accuracy of Fbx. Our results show that after an early learning period, Fbx detected higher rates of CS cancer and lower rates of clinically insignificant cancer than Sbx. Software advances allowed for even greater detection of CS disease.

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