Purpose: To establish the prognostic value of total and free prostate secretory protein of 94 amino acids (PSP94) and the PSP94-binding protein (PSPBP) following radical prostatectomy.
Experimental Design: One hundred and eighty-five serum samples were obtained from patients with localized prostate cancer prior to treatment with radical prostatectomy at Virginia Urology (Richmond, VA). Patients were followed up for a median of 48 months (range, 1-66 months) and biochemical relapse was indicated as total prostate-specific antigen (tPSA) levels increasing to > 0.1 ng/mL. The available clinical variables included initial tPSA, Gleason score, surgical margin status, and clinical stage. Total PSP94, free PSP94, and the PSPBP were quantified in the pretreatment serum using new ELISA tests (Medicorp, Inc. and Ambrilia Biopharma, Inc., Montreal, Quebec, Canada). Univariate and multivariate Cox proportional hazards models were used to assess the ability of PSP94 and PSPBP to predict time to recurrence.
Results: Thirty-one patients had biochemical recurrence. Gleason score, margin status, clinical stage, and initial tPSA significantly predicted recurrence risk (all P < 0.001). In addition, PSPBP was negatively associated with recurrence risk (P = 0.005), and, consistent with previous studies, the bound/free PSP94 ratio was positively associated with recurrence risk (P = 0.008). Multivariate analysis showed that PSPBP, as well as the bound/free PSP94 ratio, were independent predictors of biochemical relapse risk adjusting for tPSA, Gleason score, and margin status.
Conclusions: Bound/free PSP94 and PSPBP are novel and independent prognostic markers following radical prostatectomy for prostate cancer.
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http://dx.doi.org/10.1158/1078-0432.CCR-06-0625 | DOI Listing |
Sci Rep
January 2025
Department of Urology, Kyoto University School of Medicine, 54 Shougoinkawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan.
This study evaluated the impact of aspirin on the biochemical recurrence (BCR) rate following robot-assisted radical prostatectomy (RARP) in patients. A database search identified patients who underwent RARP for pT2-3N0M0 disease at any of 25 centers between 2011 and 2022, categorized into aspirin (n = 350) and control groups (n = 5857). Adjustment by 1:1 propensity score matching (PSM) and Mahalanobis distance matching (MDM) created 350 matched pairs.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Urology, Fujita Health University School of Medicine, Toyoake, Aichi, Japan.
Prostate cancer (PCa) is one of the most common cancers among men worldwide, and robot-assisted radical prostatectomy (RARP) is a widely used treatment for localized PCa. Achieving pentafecta outcomes, which include continence, potency, cancer control, free surgical margins, and no major complications, is a critical measure of surgical success and long-term prognosis. However, predicting these outcomes remains challenging.
View Article and Find Full Text PDFUrology
January 2025
Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, 430060, China; Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan, Hubei, 430060, China. Electronic address:
Objectives: To explore new metrics for assessing radical prostatectomy difficulty through a two-stage deep learning method from preoperative magnetic resonance imaging.
Methods: The procedure and metrics were validated through 290 patients consisting of laparoscopic and robot-assisted radical prostatectomy procedures from two real cohorts. The nnUNet_v2 adaptive model was trained to perform accurate segmentation of the prostate and pelvis.
Langenbecks Arch Surg
January 2025
Department for the Promotion of Medical Device Innovation, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Purpose: Assessing surgical skills is vital for training surgeons, but creating objective, automated evaluation systems is challenging, especially in robotic surgery. Surgical procedures generally involve dissection and exposure (D/E), and their duration and proportion can be used for skill assessment. This study aimed to develop an AI model to acquire D/E parameters in robot-assisted radical prostatectomy (RARP) and verify if these parameters could distinguish between novice and expert surgeons.
View Article and Find Full Text PDFInsights Imaging
January 2025
Department of Radiology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, China.
Objective: To evaluate the feasibility of utilizing artificial intelligence (AI)-predicted biparametric MRI (bpMRI) image features for predicting the aggressiveness of prostate cancer (PCa).
Materials And Methods: A total of 878 PCa patients from 4 hospitals were retrospectively collected, all of whom had pathological results after radical prostatectomy (RP). A pre-trained AI algorithm was used to select suspected PCa lesions and extract lesion features for model development.
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