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Abstract

Volume 14, Issue 3 (May 2012) 14, 349–354; 10.1038/aja.2011.140

Formalized prediction of clinically significant prostate cancer: is it possible?

Carvell T Nguyen1 and Michael W Kattan2

1 Glickman Urological & Kidney Institute, Cleveland, OH 44195, USA
2 Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH 44195, USA

Correspondence: Dr MW Kattan, (kattanm@ccf.org)

Received 3 October 2011; Revised 4 November 2011; Accepted 4 November 2011; Advance online publication 27 February 2012.

Abstract

Greater understanding of the biology and epidemiology of prostate cancer in the last several decades have led to significant advances in its management. Prostate cancer is now detected in greater numbers at lower stages of disease and is amenable to multiple forms of efficacious treatment. However, there is a lack of conclusive data demonstrating a definitive mortality benefit from this earlier diagnosis and treatment of prostate cancer. It is likely due to the treatment of a large proportion of indolent cancers that would have had little adverse impact on health or lifespan if left alone. Due to this overtreatment phenomenon, active surveillance with delayed intervention is gaining traction as a viable management approach in contemporary practice. The ability to distinguish clinically insignificant cancers from those with a high risk of progression and/or lethality is critical to the appropriate selection of patients for surveillance protocols versus immediate intervention. This chapter will review the ability of various prediction models, including risk groupings and nomograms, to predict indolent disease and determine their role in the contemporary management of clinically localized prostate cancer.

Keywords: prediction model; prostate cancer; prostatic neoplasms; screening

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Asian Journal of Andrology CN 31-1795/R ISSN 1008-682X  Copyright © 2023  Shanghai Materia Medica, Chinese Academy of Sciences.  All rights reserved.