Role of Prostate Specific Antigen Density for the Prediction of Radical Therapy Requirement in Localized Prostate Cancer
Journal Title: Üroonkoloji Bülteni - Year 2016, Vol 15, Issue 3
Abstract
Objective: Prostate specific antigen (PSA) PSA density (dPSA) is a PSA derivative used for increasing the accuracy of PSA. dPSA is calculated by dividing the prostate volume measured with transrectal ultrasonography by the total PSA value. In this study, we evaluated the role of dPSA in the prediction of radical therapy requirement in localised prostate cancer. Materials and Methods: A total of 398 patients, who underwent radical prostatectomy in our department, were included in the study. Preoperative data of the patients (demographic data, total PSA, prostate volume, dPSA and tumor percent IE on biopsy) were evaluated retrospectively. D’Amico risk stratification was performed according to the radical prostatectomy pathological examination. Evaluated parameters were compared between low-risk group (Group 1), who were candidates for active surveillance, and intermediate-high-risk group (Group 2) who were candidates for radical therapies. A dPSA cut-off value was investigated for the prediction of radical therapy requirement for patients with ROC curve analysis. Results: Mean age of the patients was similar between the two groups (62.6±6.6 vs. 62.6±58; p=0.999). PSA (8.9±6.9 vs. 5.5±1.5; p<0.05), dPSA (0.19±0.1 vs. 0.08±0.03; p<0.05) and tumor percent on biopsy (40.8±32.6 vs. 10.7±11.7; p<0.05) were significantly higher in Group 2 when compared to Group 1. ROC curve analysis revealed that patients with a dPSA value higher than 0.10 were more likely to have intermediate-high-risk disease according to postoperative the D’Amico risk stratification with 71% sensitivity and 86% specificity (AUC=0.782). Conclusion: As a result, it has been shown that a significant portion of patients with a dPSA level of ≥0.1 was included in the intermediate-high-risk group requiring radical therapies according to the postoperative pathological results. We suggest that predictive models including dPSA would better help decide for active surveillance.
Authors and Affiliations
Ozan Bozkurt, Kaan Çömez, Özgür Gürboğa, Ömer Demir, Güven Aslan, Adil Esen
Keywords
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- EP ID EP228298
- DOI 10.4274/uob.701
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