Performance of biopsy factors in predicting unfavorable disease in @entity1 eligible for XXXX according to the PRIAS criteria.

@entity1 @entity263 @entity7184 @entity5 @entity11708 @entity4623 @entity3457
BACKGROUND: To assess the added value of biopsy factors, like maximum @entity5 in a core ( @entity11708 ), @entity5 ( @entity5 ), @entity7184 ( @entity7184 ), percentage of @entity5 ( @entity5 ) and the @entity263 Research International: Active Surveillance (PRIAS) criteria in @entity1 who underwent radical prostatectomy (RP) but eligible for @entity3457 ( @entity3457 ). METHODS: From January 2002 to December 2007, 750 consecutive subjects underwent RP. We identified 147 (19.07%) @entity1 who were eligible for @entity3457 based on PRIAS criteria: clinical stage T1c or T2, PSA level of   10   ng   ml(-1), Gleason score    6, PSA-D of <0.2   ng   ml(-)(2) and one or two positive biopsy cores. We calculated the diagnostic accuracy of biopsy factors in determining pathological confirmed unfavorable disease. Decision curve analysis (DCA) were performed. RESULTS: Of all subjects, 95 @entity1 (66.43%) had favorable whereas 48 had (33.57%) unfavorable disease. On multivariate analyses, the inclusion of @entity11708 , @entity5 , @entity7184 and @entity5 significantly increased the accuracy of the base multivariate model in predicting unfavorable disease. The gain in predictive accuracy for @entity11708 in a core, @entity5 , @entity7184 and @entity5 ranged from 13 to 27%. The DCA shows that adding @entity11708 , @entity5 , @entity7184 and @entity5 resulted in a greater net benefit when the probability of ranges between 15 and 50%. The models can be applied at the cost of missing not more than 16.83% of unfavorable disease. CONCLUSIONS: Our findings suggested that the addition of these biopsy factors to PRIAS criteria has the potential to significantly increase the ability to detect unfavorable disease. @entity263 and @entity4623 advance online publication, 2 June 2015; doi:10.1038/pcan.2015.26.
