Risk factors for hemorrhagic complications following robotic-assisted partial nephrectomy.

BACKGROUND: The aim of this study was to analyze the risk factors for hemorrhagic complications in patients who underwent robotic-assisted partial nephrectomy. METHODS: We retrospectively reviewed the records of 260 patients who underwent robotic-assisted partial nephrectomy. Hemorrhagic complications were defined as bleeding, hematoma, or arteriovenous fistula requiring hemostatic medication, blood transfusion, or therapeutic intervention. Hemorrhagic complications were graded according to the modified Clavien classification system, and the hemorrhagic complication group comprised only those complications with Clavien grade II or higher. Thereafter, we investigated the presence of any relevant association between perioperative factors and hemorrhagic complications. RESULTS: Of 260 patients included in the study, 32 (12.3%) had hemorrhagic complications. The postoperative hemoglobin level was significantly lower in the hemorrhagic complication group than in the group without complications. The hemorrhagic complication group had significantly more essential blood loss and a significantly longer length of hospital stay. In the univariate analysis, type 2 diabetes mellitus, Radius-scores tumor size as maximal diameter exophytic/endophytic properties of the tumor nearness of the deepest portion of the tumor to the collecting system or renal sinus anterior (a)/posterior (p) descriptor location relative to the polar line., sum of the renal size plus renal sinus involvement in the PADUA score is a simple anatomical system that can be used to predict the risk of surgical and medical perioperative complications in patients undergoing open NSS, prolonged console time (>180 minutes), prolonged warm ischemic time (>25 minutes), and method of pedicle control were statistically significant risk factors. In the multivariate logistic regression analysis, warm ischemic time >25 minutes was the only significant risk factor for hemorrhagic complications (odds ratio, 3.51; 95% confidence interval, 1.28-9.59; p = 0.01). CONCLUSION: Patients who undergo robotic-assisted partial nephrectomy with a warm ischemic time >25 minutes are significantly more likely to have hemorrhagic complications and should hence receive careful perioperative follow-up.

Combining prostate health index and multiparametric magnetic resonance imaging may better predict extraprostatic extension after radical prostatectomy.

BACKGROUND: In patients undergoing radical prostatectomy (RP) for prostate cancer (PCa), preoperative prediction of extraprostatic extension (EPE) can facilitate patient selection for nerve-sparing procedures. Since both multiparametric magnetic resonance imaging (mpMRI) and prostate health index (PHI) have shown promise for the diagnosis and prognostication of PCa, we investigated whether a combination of mpMRI and PHI evaluations can improve the prediction of EPE after RP. METHODS: Patients diagnosed with PCa and treated with RP were prospectively enrolled between February 2017 and July 2019. Preoperative blood samples were analyzed for PHI (defined as [p2PSA/fPSA] × âˆštPSA), and mpMRI examinations were performed and interpreted by a single experienced uroradiologist retrospectively. The area under the receiver operating characteristic curve (ROC) was used to determine the performance of mpMRI, PHI, and their combination in predicting EPE after RP. RESULTS: A total of 163 patients were included for analysis. The pathological T stage was T3a or more in 59.5%. Overall staging accuracy of mpMRI for EPE was 72.4% (sensitivity and specificity: 73.2% and 71.2%, respectively). The area under the ROC of the combination of mpMRI and PHI in predicting EPE (0.785) was higher than those of mpMRI alone (0.717; p = 0.0007) and PHI alone (0.722; p = 0.0236). mpMRI showed false-negative non-EPE results in 26 patients (16%), and a PHI threshold of >40 could avoid undiagnosed EPE before RP in 21 of these 26 patients. CONCLUSION: The combination of PHI and mpMRI may better predict the EPE preoperatively, facilitating preoperative counseling and tailoring the need for nerve-sparing RP.

Patients with preoperative asymptomatic pyuria are not prone to develop febrile urinary tract infection after ureteroscopic lithotripsy.

BACKGROUND: This study aimed to evaluate the association of asymptomatic pyuria before ureterorenoscopic lithotripsy (URSL) with postoperative febrile urinary tract infection (UTI). METHODS: This observational case-control study identified the patients undergoing URSL for ureteral stones between May 2011 and October 2015. The included patients were classified into two groups: the asymptomatic pyuria group (6-50 white blood cells [WBCs]/high-power field [HPF]) and the non-pyuria group (≤ 5 WBCs/HPF). All data were collected by reviewing medical records. Postoperative outcomes were collected in terms of febrile UTI, emergency visits, and stone-free rate. RESULTS: A total of 232 patients were included, 101 in the pyuria group, 131 in the non-pyuria group. Two (0.9%) patients developed febrile UTI after URSL and 12 (5.2%) patients visited emergency department for URSL-related symptoms. The overall stone-free rate was 90.9%. There was no significant difference between the pyuria and non-pyuria groups regarding febrile UTI, emergency visits, and stone-free rate. Multivariate analysis revealed that pyuria was neither significantly associated with postoperative febrile UTI (OR = 1.03, 95% CI = 0.06-18.10, P = 0.98), nor with emergency visits (OR = 0.48, 95% CI = 0.13-1.85, P = 0.29). CONCLUSIONS: Compared to the patients with sterile urine prior to URSL, those with asymptomatic pyuria were not prone to develop febrile UTI after URSL.

The Prostate Health Index aids multi-parametric MRI in diagnosing significant prostate cancer.

To evaluate the performance of the Prostate Health Index (PHI) in magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) fusion prostate biopsy for the detection of clinically significant prostate cancer (csPCa). We prospectively enrolled 164 patients with at least one Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) ≥ 3 lesions who underwent MRI-TRUS fusion prostate biopsy. Of the PSA-derived biomarkers, the PHI had the best performance in predicting csPCa (AUC 0.792, CI 0.707-0.877) in patients with PI-RADS 4/5 lesions. Furthermore, the predictive power of PHI was even higher in the patients with PI-RADS 3 lesions (AUC 0.884, CI 0.792-0.976). To minimize missing csPCa, we used a PHI cutoff of 27 and 7.4% of patients with PI-RADS 4/5 lesions could have avoided a biopsy. At this level, 2.0% of cases with csPCa would have been missed, with sensitivity and NPV rates of 98.0% and 87.5%, respectively. However, the subgroup of PI-RADS 3 was too small to define the optimal PHI cutoff. PHI was the best PSA-derived biomarker to predict csPCa in MRI-TRUS fusion prostate biopsies in men with PI-RADS ≥ 3 lesions, especially for the patients with PI-RADS 3 lesions who gained the most value.

Prostate health index density predicts aggressive pathological outcomes after radical prostatectomy in Taiwanese patients.

BACKGROUND: There are models to predict pathological outcomes based on established clinical and prostate-specific antigen (PSA)-derived parameters; however, they are not satisfactory. p2PSA and its derived biomarkers have shown promise for the diagnosis and prognosis of prostate cancer (PCa). The aim of this study was to investigate whether p2PSA-derived biomarkers can assist in the prediction of aggressive pathological outcomes after radical prostatectomy (RP). METHODS: We prospectively enrolled patients who were diagnosed with PCa and treated with RP between February 2017 and December 2018. Preoperative blood samples were analyzed for tPSA, free PSA (fPSA), percentage of fPSA (%fPSA), [-2]proPSA (p2PSA), and percentage of p2PSA (%p2PSA). Prostate health index (PHI) was calculated as (p2PSA/fPSA) × âˆštPSA. Prostate volume was determined by transrectal ultrasound using the ellipsoid formula, and PHI density was calculated as PHI/prostate volume. The areas under the receiver operating characteristic curve were estimated for various PSA/p2PSA derivatives. Aggressive pathological outcomes measured after RP were defined as pathological T3 or a Gleason score (GS) >6 as determined in RP specimens. RESULTS: One hundred and forty-four patients were included for analysis. Postoperative GS was >6 in 86.1% of the patients, and pT stage was T3a or more in 54.2%. Among all PSA- and p2PSA-derived biomarkers, PHI density was the best biomarker to predict aggressive pathological outcomes after RP. The odds ratio of having an aggressive pathological outcome of RP was 8.796 (p = 0.001). In multivariate analysis, adding %fPSA to base model did not improve the accuracy (area under curve), but adding PHI and PHI density to base model improved the accuracy by 2% and 16%, respectively, in predicting pT3 stage or GS ≥ 7. The risk of pT3 stage or GS ≥ 7 was 20.8% for PHI density <1.125, and 64.6% for PHI density >1.125 (sensitivity: 74.6% and specificity: 88.9%). CONCLUSION: PHI density may further aid in predicting aggressive pathological outcomes after RP. This biomarker may be useful in preoperative counseling and may have potential in decision making when choosing between definitive treatment and active surveillance of newly diagnosed PCa.

Prostate Health Index outperforms other PSA derivatives in predicting a positive biopsy in men with tPSA <10 ng/mL: Largest prospective cohort in Taiwan.

BACKGROUND: Few prospective studies have focused on the performance of the Prostate Health Index (PHI) in Asian populations. Therefore, we aimed to evaluate the performance of the PHI in predicting prostate cancer (PCa) compared with standard prostate-specific antigen (PSA) tests. METHODS: We prospectively enrolled patients with suspected PCa with a total PSA (tPSA) level 4 to 10 ng/mL or tPSA <4 ng/mL and a suspicious digital rectal examination between February 2017 and September 2018. All of the patients underwent a 12-core transrectal ultrasound-guided prostate biopsy. Prebiopsy blood samples were analyzed for tPSA, free PSA (fPSA), percentage of fPSA (%fPSA), [-2]proPSA (p2PSA), and percentage of p2PSA (%p2PSA). The PHI was calculated as (p2PSA/fPSA) × âˆštPSA. The areas under the receiver operating characteristic curve (AUCs) were estimated for the PSA derivatives in addition to their specificities at a prespecified sensitivity of 90%. RESULTS: Of the 307 enrolled patients, 95 (30.9%) had PCa on biopsy. Excluding fPSA, all of the PSA derivatives were significantly different between the positive and negative biopsy groups. Of the various derivatives, the PHI (AUC: 0.783) showed the best performance in predicting the results of the initial biopsy compared with tPSA (AUC: 0.611). At a sensitivity of 90%, the PHI had the best specificity of 46.7% compared with 23.2% for tPSA. Using a PHI cutoff value of 35.15 for biopsy, 108 (35.2%) patients could have avoided undergoing a biopsy. To detect Gleason score ≥ 7 disease at 90% sensitivity, the threshold for PHI was 36.96 with a specificity of 52.1%. CONCLUSION: PHI was the best biomarker among the PSA derivatives in predicting PCa at biopsy in men with tPSA < 10 ng/mL. The risk of a Gleason score ≥ 7 increased with increasing PHI.