A Matched-Pair Analysis after Robotic and Retropubic Radical Prostatectomy: A New Definition of Continence and the Impact of Different Surgical Techniques

Background: Radical prostatectomy is considered the gold-standard treatment for patients with localized prostate cancer. The literature suggests there is no difference in oncological and functional outcomes between robotic-assisted radical prostatectomy (RARP) and open (RRP). (2) Methods: The aim of this study was to compare continence recovery rates after RARP and RRP measured with 24 h pad weights and the International Consultation on Incontinence Questionnaire—Short Form (ICIQ-SF). After matching the population (1:1), 482 met the inclusion criteria, 241 patients per group. Continent patients with a 24 h pad test showing <20 g of urinary leakage were considered, despite severe incontinence, and categorized as having >200 g of urinary leakage. (3) Results: There was no difference between preoperative data. As for urinary continence (UC) and incontinence (UI) rates, RARP performed significantly better than RRP based on objective and subjective results at all evaluations. Univariable and multivariable Cox Regression Analysis pointed out that the only significant predictors of continence rates were the bilateral nerve sparing technique (1.25 (CI 1.02,1.54), p = 0.03) and the robotic surgical approach (1.42 (CI 1.18,1.69) p ≤ 0.001). (4) Conclusions: The literature reports different incidences of UC depending on assessment and definition of continence “without pads” or “social continence” based on number of used pads per day. In this, our first evaluation, the advantage of objective measurement through the weight of the 24 h and subjective measurement with the ICIQ-SF questionnaire best demonstrates the difference between the two surgical techniques by enhancing the use of robotic surgery over traditional surgery.

Prostate Surface Distension and Tumor Texture Descriptors From Pre-Treatment MRI Are Associated With Biochemical Recurrence Following Radical Prostatectomy: Preliminary Findings

Objective

To derive and evaluate the association of prostate shape distension descriptors from T2-weighted MRI (T2WI) with prostate cancer (PCa) biochemical recurrence (BCR) post-radical prostatectomy (RP) independently and in conjunction with texture radiomics of PCa.

Methods

This retrospective study comprised 133 PCa patients from two institutions who underwent 3T-MRI prior to RP and were followed up with PSA measurements for ≥3 years. A 3D shape atlas-based approach was adopted to derive prostate shape distension descriptors from T2WI, and these descriptors were used to train a random forest classifier (C_S) to predict BCR. Texture radiomics was derived within PCa regions of interest from T2WI and ADC maps, and another machine learning classifier (C_R) was trained for BCR. An integrated classifier C_S+R was then trained using predictions from C_S and C_R. These models were trained on D₁ (N = 71, 27 BCR+) and evaluated on independent hold-out set D₂ (N = 62, 12 BCR+). C_S+R was compared against pre-RP, post-RP clinical variables, and extant nomograms for BCR-free survival (bFS) at 3 years.

Results

C_S+R resulted in a higher AUC (0.75) compared to C_R (0.70, p = 0.04) and C_S (0.69, p = 0.01) on D₂ in predicting BCR. On univariable analysis, C_S+R achieved a higher hazard ratio (2.89, 95% CI 0.35–12.81, p < 0.01) compared to other pre-RP clinical variables for bFS. C_S+R, pathologic Gleason grade, extraprostatic extension, and positive surgical margins were associated with bFS (p < 0.05). C_S+R resulted in a higher C-index (0.76 ± 0.06) compared to CAPRA (0.69 ± 0.09, p < 0.01) and Decipher risk (0.59 ± 0.06, p < 0.01); however, it was comparable to post-RP CAPRA-S (0.75 ± 0.02, p = 0.07).

Conclusions

Radiomic shape descriptors quantifying prostate surface distension complement texture radiomics of prostate cancer on MRI and result in an improved association with biochemical recurrence post-radical prostatectomy.

Prostate cancer biomarkers: a practical review based on different clinical scenarios

Traditionally, diagnosis and staging of prostate cancer (PCa) have been based on prostate-specific antigen (PSA) level, digital rectal examination (DRE), and transrectal ultrasound (TRUS) guided prostate biopsy. Biomarkers have been introduced into clinical practice to reduce the overdiagnosis and overtreatment of low-grade PCa and increase the success of personalized therapies for high-grade and high-stage PCa. The purpose of this review was to describe available PCa biomarkers and examine their use in clinical practice. A nonsystematic literature review was performed using PubMed and Scopus to retrieve papers related to PCa biomarkers. In addition, we manually searched websites of major urological associations for PCa guidelines to evaluate available evidence and recommendations on the role of biomarkers and their potential contribution to PCa decision-making. In addition to PSA and its derivates, thirteen blood, urine, and tissue biomarkers are mentioned in various PCa guidelines. Retrospective studies have shown their utility in three main clinical scenarios: (1) deciding whether to perform a biopsy, (2) distinguishing patients who require active treatment from those who can benefit from active surveillance, and (3) defining a subset of high-risk PCa patients who can benefit from additional therapies after RP. Several validated PCa biomarkers have become commercially available in recent years. Guidelines now recommend offering these tests in situations in which the assay result, when considered in combination with routine clinical factors, is likely to affect management. However, the lack of direct comparisons and the unproven benefits, in terms of long-term survival and cost-effectiveness, prevent these biomarkers from being integrated into routine clinical use.

The role of metabolic syndrome in high grade prostate cancer: development of a clinical nomogram

BACKGROUND

The aim of our study is to develop a clinical nomogram including metabolic syndrome status for the prediction of high-grade prostate cancer (HG PCa).

METHODS

A series of men at increased risk of PCa undergoing prostate biopsies were enrolled in a single center. Demographic and clinical characteristics of the patients were recorded. Metabolic syndrome was defined according to the adult treatment panel III. A nomogram was generated based on the logistic regression model and used to predict high grade prostate cancer defined as grade group ≥3 (ISUP 2014). ROC curves, calibration plots and decision curve analysis were used to evaluate the performance of the nomogram.

RESULTS

Overall, 738 patients were enrolled. Greater than or equal to 294/738 (40%) of the patients presented PCa and of those patients, 84/294 (39%) presented high grade disease (Grade Group ≥3). On multivariate analysis, DRE (OR: 3.24, 95% CI: 1.80-5.84), PSA (OR: 1.10, 95% CI: 1.05-1.16), PV (OR: 0.98, 95% CI: 0.97-0.99) and MetS (OR: 2.02, 95% CI: 1.13-3.59) were predictors of HG PCa. The nomogram based on the model presented good discrimination (AUC: 0.76), good calibration (Hosmer-Lemeshow Test, P>0.05) and a net benefit in the range of probabilities between 10% and 70%.

CONCLUSIONS

Metabolic syndrome is highly prevalent in patients at risk of prostate cancer and is particularly associated with high-grade prostate cancer. Our nomogram offers the possibility to include metabolic status in the assessment of patients at risk of prostate cancer to identify men who may have a high-grade form of the disease. External validation is warranted before its clinical implementation.

Performance of prostate multiparametric MRI for prediction of prostate cancer extra-prostatic extension according to NCCN risk categories: implication for surgical planning

BACKGROUND

Prediction of extra-prostatic extension (EPE) in men undergoing radical prostatectomy (RP) is of utmost importance. Great variability in the performance of multiparametric magnetic resonance imaging (mpMRI) has been reported for prediction of EPE. The present study aimed to determine the diagnostic performance of mpMRI for predicting EPE in different National Comprehensive Cancer Network (NCCN) risk categories.

METHODS

Overall 664 patients who underwent radical prostatectomy with a staging mpMRI were enrolled in this single-center, retrospective study. Patients with mpMRI report non-compliant with PI-RADSv2.0, were excluded. Patients were stratified according to NCCN criteria: very low/low (VLR-LR) to High Risk (HR) in order to assess final pathology EPE rates (focal and established). Sensitivity, specificity, positive and negative predictive values of staging mpMRI were computed in each group. Univariable and multivariable analysis were used to evaluate predictors of positive surgical margins.

RESULTS

Pathological evaluation demonstrated established and focal EPE in 60 (9%) and 106 (16%) patients, respectively, while mpMRI suspicion for EPE was present in 180 (27%) patients. Age, preoperative PSA, PSA density, number of positive cores, NCCN groups, prostate volume, mpMRI suspicion for EPE, PIRADSv2.0 and lesion size differed significantly between the patients with any EPE and without EPE (all P≤0.05). The sensitivity of mpMRI in detecting any EPE varied from 12% (95% CI: 0.6-53%) in VLR-LR to 83% (66-93%) in HR while the corresponding values for the specificity were 92% (85-96%) and 63% (45-78%), respectively. Patients with false-negative mpMRI EPE prediction were more likely to have positive surgical margins in univariable (OR: 2.14; CI: 1.18, 3.87) as well as multivariable analysis adjusting for NCCN risk categories (OR: 1.97; CI: 1.08, 3.60).

CONCLUSIONS

The performance of mpMRI for prediction of EPE varies greatly between different NCCN risk categories with a low positive predicting value in patients at low to favorable intermediate risk and a low negative predictive value in patients at Unfavorable intermediate to high risk PCa. Given that mpMRI EPE misdiagnosis could have a negative impact on oncological and functional outcomes, NCCN risk categories should be considered when interpreting mpMRI findings in PCa patients.