The importance of PSA-Density in active surveillance for prostate cancer

• Main Authors: Caner Ediz, Serkan Akan, Muhammed Cihan Temel, Omer Yilmaz
• Format: Article
• Language: English
• Published: PAGEPress Publications 2020-06-01
• Series: Archivio Italiano di Urologia e Andrologia
• Subjects: Prostate cancer, Active surveillance, PSA Density, Definitive treatment
• Online Access: https://www.pagepressjournals.org/index.php/aiua/article/view/8756

Objective: In this study, we aimed to determine the predictive factor for additional treatment requirement in active surveillance (AS) for patients with low or very low-risk prostate cancer (PCa) and we investigated the effect of tumor burden by total core involvement rate in biopsy to predict of need for additional treatment. Material and methods: 107 patients with PCa in AS between 2005 and 2018 have been evaluated retrospectively. Groups were divided into two groups according to the need for additional treatment. Group 1 received additional treatment, group 2 did not receive additional treatments and active surveillance was continued. Patient’s total prostate-specific antigen (tPSA), prostate-specific antigen density (PSA-D), total core involvement count, quantity and rate at biopsy pathology results and follow-up period were recorded and compared in the two groups. Results: The current cohort includes 107 patients. Mean age at diagnosis was 63.01years. Mean tPSA values at diagnosis were 6.09 ng/mL and 5.2 ng/mL in the group 1 and group 2, respectively. Mean follow-up period was 38.1 months (range, 12 to 134 months). Only PSA-D measurement significantly predicted need for additional treatment (p = 0.017). ROC analysis showed that the optimal threshold was 0.13 ng/mL/cc (sensitivity: 70.8%; specificity: 57.1%). Additional treatment requirement was not detected in patients with PSA-D cut-off level less than 0.07 ng/mL/cc. Conclusions: Total tumor burden of less than 5% is safe for patients with low or very low-risk PCa in AS. A 0.13 ng/mL/cc cut-off level of PSA-D can predict to need for additional treatment in patients managed by AS.