Original Article

Clinical Research

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

  • Prostate Cancer and Prostatic Diseases volume 20, pages 436441 (2017)
  • doi:10.1038/pcan.2017.34
  • Download Citation
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Abstract

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 (7/2007−12/2010) accounted 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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Acknowledgements

This research was supported by the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute, Center for Cancer Research, and the Center for Interventional Oncology. NIH and Philips Healthcare have a cooperative research and development agreement. NIH and Philips share intellectual property in the field. This research was also made possible through the NIH Medical Research Scholars Program, a public-private partnership supported jointly by the NIH and generous contributions to the Foundation for the NIH by the Doris Duke Charitable Foundation (Grant #2014194), the American Association for Dental Research, the Colgate-Palmolive Company, Genentech, and other private donors. For a complete list, visit the foundation website at http://www.fnih.org.

Author information

Affiliations

  1. Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    • B Calio
    • , A Sidana
    • , D Sugano
    • , A Jain
    • , M Maruf
    •  & P Pinto
  2. Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    • M Merino
  3. Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    • S Gaur
    • , P Choyke
    •  & B Turkbey
  4. Center for Interventional Oncology, National Cancer Institute and Clinical Center, National Institutes of Health, Bethesda, MD, USA

    • S Xu
    • , P Yan
    • , J Kruecker
    •  & B Wood

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Competing interests

The authors declare no conflict of interest.

Corresponding author

Correspondence to B Calio.