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Predictive models for worsening prognosis in potential candidates for active surveillance of presumed low-risk prostate cancer

  • Urology – Original Paper
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Abstract

Purpose

Low-risk prostate cancer patients clinically eligible for active surveillance can also be managed surgically. We evaluated the pathologic outcomes for this cohort that was treated by radical prostatectomy and devised nomograms to predict patients at risk of upgrading and/or upstaging.

Materials and methods

Seven hundred and fifty patients treated by radical prostatectomy from Jan 2005 to the present fulfilled conventional active surveillance criteria and formed the study cohort. Preoperative data on standard clinicopathologic parameters were available. The radical prostatectomy specimens were graded and staged, and any upgrading to Gleason sum >6 or upstaging to ≥pT3 (‘worsening prognosis’) were noted. Multivariable logistic regression models were used to develop predictive nomograms.

Results

Of the 750 patients, 303 (40.4%) patients were either upgraded or upstaged. Multivariable analysis found that preoperative PSA, number of positive cores, and prostate volume were significantly predictive of worsening prognosis and formed the nomogram criteria.

Conclusions

Of patients deemed eligible for active surveillance based on conventional criteria, 40.4% have worse prognostic factors after radical prostatectomy. Current active surveillance criteria may be too relaxed, and the use of nomograms which we have devised, may aid in counseling primary prostate cancer patients considering active surveillance as their therapy of choice.

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Acknowledgments

Dr. Prasanna Sooriakumaran is the ACMI Corp. Endourological Society fellow and also receives financial support from Prostate UK; Dr. Paul Christos is partially supported by the following grant: Clinical Translational Science Center (CTSC) (UL1-RR024996); Dr. Ashutosh Tewari is the endowed Ronald P. Lynch Professor of Urologic-Oncology, the Director of the Prostate Cancer Institute, and Director of the Lefrak Center for Robotic Surgery, and has received grants in the past from Intuitive Surgical Inc. and the National Institute of Health. However, this work was not supported by such grants.

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Authors and Affiliations

  1. Department of Urology, Lefrak Center of Robotic Surgery & Institute of Prostate Cancer, Weill Cornell Medical College, James Buchanan Brady Foundation, New York, NY, 10065, USA

    Prasanna Sooriakumaran, Abhishek Srivastava, Sonal Grover & Ashutosh Tewari

  2. Department of Statistics & Public Health, Weill Cornell Medical College, New York, NY, USA

    Paul Christos

  3. Department of Pathology, Weill Cornell Medical College, New York, NY, USA

    Maria Shevchuk

Authors
  1. Prasanna Sooriakumaran
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  2. Abhishek Srivastava
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  3. Paul Christos
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  4. Sonal Grover
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  5. Maria Shevchuk
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  6. Ashutosh Tewari
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Corresponding author

Correspondence to Ashutosh Tewari.

Additional information

Prasanna Sooriakumaran and Abhishek Srivastava contributed equally to the work in this manuscript.

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Sooriakumaran, P., Srivastava, A., Christos, P. et al. Predictive models for worsening prognosis in potential candidates for active surveillance of presumed low-risk prostate cancer. Int Urol Nephrol 44, 459–470 (2012). https://doi.org/10.1007/s11255-011-0020-0

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  • DOI: https://doi.org/10.1007/s11255-011-0020-0

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