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Updated: Mar 13, 2026
Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Evaluation of predictors of unfavorable pathological features in men eligible for active surveillance using radical
Kei Mizuno1, Takahiro Inoue2, Hidefumi Kinoshita3
1Department of Urology, Japanese Red Cross Otsu Hospital, Otsu.
Objective:
Active surveillance has emerged as an alternative to immediate treatment in men with favorable-risk prostate cancer; however, consensus about defining the appropriate candidates is still lacking. To examine the factors predicting unfavorable pathology among active surveillance candidates, we assessed low-risk radical prostatectomy specimens.
Methods:
This retrospective study included 1753 men who had undergone radical prostatectomy at six independent institutions in Japan from 2005 to 2011. Patients who met the active surveillance criteria were categorized depending on the pathological features of the radical prostatectomy specimens. 'Reclassification' was defined as upstaging (≥pT3) or upgrading (radical prostatectomy Gleason score ≥7), and 'adverse pathology' was defined as pathological stage ≥pT3 or radical prostatectomy Gleason score ≥4 + 3. Multivariate analysis was used to analyze the preoperative factors for reclassification and adverse pathology. The rates of reclassification and adverse pathology were evaluated by classifying patients according to biopsy core numbers.
Results:
The active surveillance criteria were met by 284 cases. Reclassification was identified in 154 (54.2%) cases, while adverse pathology in 60 (21.1%) cases. Prostate-specific antigen density and percentage of positive cores were independently associated with reclassification and adverse pathology. The rates of reclassification and adverse pathology were significantly higher among patients with <10 biopsy cores than among others. Thus, focusing on 149 patients with ≥10 biopsy cores, prostate-specific antigen density was the only independent predictor of unfavorable pathological features. The receiver operating characteristic curve analysis determines an optimal cut-off value of prostate-specific antigen density as 0.15 ng/ml2.
Conclusions:
Prostate-specific antigen density is the most important predictor of unfavorable pathological features in active surveillance candidates.
