OBJECTIVE: To assess the ability of current nomograms to predict disease progression at repeat biopsy or at delayed radical prostatectomy (RP) in a prospectively accrued cohort of patients managed by active surveillance (AS).
MATERIALS AND METHODS: A total of 273 patients meeting low-risk criteria who were managed by AS and who underwent multiple biopsies and/or delayed RP were included in the study. The Kattan (base, medium and full), Steyerberg, Nakanishi and Chun nomograms were used to calculate the likelihood of indolent disease ('nomogram probability') as well as to predict 'biopsy progression' by grade or volume, 'surgical progression' by grade or stage, or 'any progression' on repeat biopsy or surgery. We evaluated the associations between each nomogram probability and each progression outcome using logistic regression with (area under the receiver-operating characteristic curve (AUC) values and decision curve analysis.
RESULTS: The nomogram probabilities of indolent disease were lower in patients with biopsy progression (P < 0.01) and any progression on repeat biopsy or surgical pathology (P < 0.05). In regression analyses, nomograms showed a modest ability to predict biopsy progression, adjusted for total number of biopsies (AUC range 0.52-0.67) and any progression (AUC range 0.52-0.70). Decision curve analyses showed that all the nomograms, except for the Kattan base model, have similar value in predicting biopsy progression and any progression. Nomogram probabilities were not associated with surgical progression in a subgroup of 58 men who underwent delayed RP.
CONCLUSIONS: Existing nomograms have only modest accuracy in predicting the outcomes of patients undergoing AS. Improvements to existing nomograms should be made before they are implemented in clinical practice and used to select patients for AS.
Written by:
Wang SY, Cowan JE, Cary KC, Chan JM, Carroll PR, Cooperberg MR. Are you the author?
Department of Urology, University of California, Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA.
Reference: BJU Int. 2013 Nov 6. Epub ahead of print.
doi: 10.1111/bju.12554
PubMed Abstract
PMID: 24712895
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