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The evaluation and staging of clinically localized prostate cancer

Nature Clinical Practice Urology volume 2, pages 356–357 (2005)Cite this article

Appropriate counseling of patients before definitive treatment for localized prostate cancer requires an accurate and reliable estimate of disease stage. The efficacy of the various treatment modalities available for prostate cancer is directly dependent upon the extent of local disease burden. Unfortunately, urologists have only a limited number of tools with which to stage clinically localized prostate cancer. Serum PSA level, digital rectal examination (DRE), and biopsy GLEASON SUM are universally used to this end. As a result of the stage migration toward more localized disease observed since the beginning of widespread PSA screening, however, DRE results and serum PSA levels are becoming less useful in stratifying patients. Most patients present with a relatively low PSA level and a benign-feeling prostate on DRE. Even with the use of serum PSA level, biopsy information, and DRE, understaging frequently occurs.1 The shortcomings of these tests make counseling patients on their likelihood of being cured a challenge. The need for more accurate clinical staging has prompted urologists to investigate other avenues for characterizing the local extent of prostate cancer.

A spectrum of techniques and technologies is currently available to complement PSA, DRE, and biopsy information. Some tools, in fact, can be utilized even without further data collection. Nomograms and predictive tables are designed to help the clinician accurately assess the likelihood of a certain stage or outcome, based on a patient's clinical parameters. The Partin Tables are among the best recognized of these tools, and were updated in 2001 for more accurate application to patients treated during the PSA era.2 These tables combine a patient's pretreatment PSA, clinical stage, and biopsy Gleason sum to estimate the likelihood of various pathologic stages upon definitive treatment with radical prostatectomy. Perhaps of more value to patients, however, are the nomograms created by Kattan et al., which estimate the risk of disease progression.3 Several of the Kattan nomograms are available online and allow easy calculation of pretreatment or post-treatment risk of progression.4 Using more advanced technology, artificial neural networks have recently been employed to utilize clinical data to determine clinical stage. In Han et al.'s 2001 study of 5,744 men treated for prostate cancer, ROC CURVE comparisons showed an artificial neural network to be slightly superior to nomograms based on logistic regression.5 The improvement in predictive accuracy was minimal, but nevertheless indicates a favorable future role for this type of analysis in the evaluation of prostate cancer.

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Authors and Affiliations

  1. Urology,

    Robert E Mitchell, Mark H Katz, James M McKiernan & Mitchell C Benson

  2. Urology,

    Robert E Mitchell, Mark H Katz, James M McKiernan & Mitchell C Benson

  3. Columbia University, New York, NY, USA

    Robert E Mitchell, Mark H Katz, James M McKiernan & Mitchell C Benson

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  1. Robert E Mitchell
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  2. Mark H Katz
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  4. Mitchell C Benson
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Correspondence to Mitchell C Benson.

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Mitchell, R., Katz, M., McKiernan, J. et al. The evaluation and staging of clinically localized prostate cancer. Nat Rev Urol 2, 356–357 (2005). https://doi.org/10.1038/ncpuro0260

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