Percentage of cancer involvement in positive cores can predict unfavorable disease in men with low-risk prostate cancer but eligible for the prostate cancer international: Active surveillance criteria

AbstractObjectives ntify predictive factors of unfavorable disease and of biochemical failure in patients treated with radical prostatectomy but eligible for active surveillance (AS) according to Prostate Cancer Research International: Active Surveillance (PRIAS) criteria. We aimed to introduce and validate the percentage of cancer involvement in positive cores (CIPC) as potential worse predictive factor. s anuary 2002 to December 2007, 750 consecutive subjects underwent radical prostatectomy at a single institution. We identified 147 (19.05%) patients who were eligible for AS based on PRIAS criteria: clinical stage T1c or T2 disease, prostate-specific antigen level of≤10 ng/ml, Gleason score≤6, prostate-specific antigen-D of<0.2 ng/ml2, and fewer than 3 positive biopsy cores. CIPC was included in the analysis. s 147 patients, 95 (66.43%) patients had favorable disease, whereas 48 (33.57%) had unfavorable disease. In multivariate logistic regression, maximum cancer length (odds ratio 12.52, P<0.01) and CIPC (odds ratio 1.70, P<0.01) represented independent predictors of unfavorable prostate cancer. The area under the receiver operating characteristics curve analysis revealed significantly higher performance after including CIPC to the PRIAS criteria (0.61 vs. 0.94, P<0.01). A cutoff of 0.4 mm of CIPC was set to predict unfavorable disease with 93% specificity, 76% sensibility, and 87% accuracy based on the receiver operating characteristics curve analysis. Finally, the 3- and 5-years biochemical recurrence (BCR)-free survival were significantly lower in subjects with CIPC≥0.4 mm, 88.4 % and 81.0% vs. 97.8% and 95.7%, respectively (P< 0.01). sions ndings suggest that the inclusion of CIPC to the prostate biopsy features could be helpful to avoid misclassification in patients eligible for AS according to the PRIAS criteria.