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Title: Evaluation of models predicting insignificant prostate cancer to select men for active surveillance of prostate cancer.
Authors: Wong, L M;Neal, D E;Finelli, A;Davis, S;Bonner, C;Kapoor, J;Trachtenberg, J;Thomas, B;Hovens, C M;Costello, Anthony J;Corcoran, N M
Affiliation: 1] Department of Urology and Surgery, St Vincent's Hospital, Fitzroy, Victoria , Australia [2] Department of Urology and Surgery, Austin Health, University of Melbourne, Heidelberg, Victoria, Australia.
Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Division of Uro-oncology, Department of Surgical Oncology, Princess Margaret Hospital, University of Toronto, Toronto, Ontario, Canada.
The Australian Prostate Cancer Centre at Epworth and Departments of Urology and Surgery, Royal Melbourne Hospital and University of Melbourne, Parkville, Victoria, Australia.
Issue Date: 10-Feb-2015
Citation: Prostate Cancer and Prostatic Diseases 2015; 18(2): 137-43
Abstract: In an era of personalized medicine, individualized risk assessment using easily available tools on the internet and the literature are appealing. However, uninformed use by clinicians and the public raises potential problems. Herein, we assess the performance of published models to predict insignificant prostate cancer (PCa), using a multi-national low-risk population that may be considered for active surveillance (AS) based on contemporary practice.Data on men suitable for AS but undergoing upfront radical prostatectomy were pooled from three international academic institutions in Cambridge (UK), Toronto (Canada) and Melbourne (Australia). Four predictive models identified from literature review were assessed for their ability to predict the presence of four definitions of insignificant PCa. Evaluation was performed using area under the curve (AUC) of receiver operating characteristic curves and Brier scores for discrimination, calibration curves and decision curve analysis.A cohort of 460 men meeting the inclusion criteria of all four nomograms was identified. The highest AUCs calculated for any of the four models ranged from 0.618 to 0.664, suggesting weak positive discrimination at best. Models had best discriminative ability for a definition of insignificant disease characterized by organ-confined Gleason score ⩽6 with a total volume ⩽0.5 ml or 1.3 ml. Calibration plots showed moderate range of predictive ability for the Kattan model though this model did not perform well at decision curve analysis.External assessment of models predicting insignificant PCa showed moderate performance at best. Uninformed interpretation may cause undue anxiety or false reassurance and they should be used with caution.
Internal ID Number: 25667108
DOI: 10.1038/pcan.2015.1
Type: Journal Article
Appears in Collections:Journal articles

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