The prostate cancer risk stratification (ProCaRS) project: Recursive partitioning risk stratification analysis

Abstract

Background The Genitourinary Radiation Oncologists of Canada (GUROC) published a three-group risk stratification (RS) system to assist prostate cancer decision-making in 2001. The objective of this project is to use the ProCaRS database to statistically model the predictive accuracy and clinical utility of a proposed new multi-group RS schema. Methods The RS analyses utilized the ProCaRS database that consists of 7974 patients from four Canadian institutions. Recursive partitioning analysis (RPA) was utilized to explore the sub-stratification of groups defined by the existing three-group GUROC scheme. 10-fold cross-validated C-indices and the Net Reclassification Index were both used to assess multivariable models and compare the predictive accuracy of existing and proposed RS systems, respectively. Results The recursive partitioning analysis has suggested that the existing GUROC classification system could be altered to accommodate as many as six separate and statistical unique groups based on differences in BFFS (C-index 0.67 and AUC 0.70). GUROC low-risk patients would be divided into new favorable-low and low-risk groups based on PSA ≤6 and PSA >6. GUROC intermediate-risk patients can be subclassified into low-intermediate and high-intermediate groups. GUROC high-intermediate-risk is defined as existing GUROC intermediate-risk with PSA >=10 AND either T2b/c disease or T1T2a disease with Gleason 7. GUROC high-risk patients would be subclassified into an additional extreme-risk group (GUROC high-risk AND (positive cores ≥87.5% OR PSA >30). Conclusions Proposed RS subcategories have been identified by a RPA of the ProCaRS database. © 2013 Elsevier Ireland Ltd. All rights reserved.