Comparison of partial and total cystectomy for colorectal cancer with histologically confirmed bladder invasion.

BACKGROUND: Although organs are preserved and quality of life is improved, insufficient evidence is available for the oncologic safety of partial cystectomy in patients with colorectal cancer with suspected bladder invasion. Therefore, we aimed to compare partial and total cystectomy outcomes in patients with pathologically confirmed or clinically suspected bladder invasion. METHODS: Patients with colorectal cancer with suspected bladder invasion who underwent R0 resection from 2000 to 2020 were evaluated. Long-term outcomes were determined in patients with histologically confirmed bladder invasion. RESULTS: Of the 151 consecutive patients, 96 (64.6%) had histologically confirmed bladder involvement, and 105 (69.5%) underwent partial cystectomy. Operative time, estimated blood loss, and reoperation rate in ≤30 days were significantly worse in the total cystectomy group than in the partial cystectomy group. The overall recurrence rate was significantly higher in the total cystectomy group than in the partial cystectomy group (39.1% vs 21.9%; P = .046). Five-year overall survival (75.8% vs 53.2%; P = .006) rates were higher in the partial cystectomy group than in the total cystectomy group; however, disease-free survival (60.8% vs 41.6%; P = .088) rates were similar in patients with suspected bladder invasion. In patients with histologically confirmed bladder invasion, 5-year overall survival rates (78.1% vs 52.1%; P = .017) were higher in the partial cystectomy group than in the total cystectomy group; however, disease-free survival rates (53.4% vs 41.2%; P = .220) did not differ significantly. CONCLUSION: R0 resection is associated with favorable long-term outcomes in patients with locally advanced colorectal cancer. If R0 resection is possible, partial cystectomy is considered safe.

Evaluation of histological variants of upper tract urothelial carcinoma as prognostic factor after radical nephroureterectomy.

PURPOSE: To evaluate the impact of variant histology on patients with upper tract urothelial carcinoma (UTUC) survival outcomes. MATERIALS AND METHODS: A total of 519 patients underwent radical nephroureterectomy without neoadjuvant therapy for UTUC at a single institution between May 2003 and December 2019. Multivariate Cox regression analysis evaluated the impact of variant histology on progression-free survival (PFS), cancer-specific survival (CSS), and overall survival (OS). RESULTS: Among 84 patients (16.2%) with variant histology, the most frequent variant type was squamous cell differentiation (64.3%), followed by glandular differentiation (25.0%) and sarcomatoid variant (2.4%). They showed pathologically advanced T stage (for ≥ T3, 59.5% vs 33.3%, p < 0.001), higher tumor grade (96.4% vs 85.7%, p = 0.025), and higher rates of lymph node metastasis (17.9% vs 7.8%, p = 0.015), angiolymphatic invasion (41.7% vs 25.7%, p = 0.003), tumor necrosis (57.1% vs 29.0%, p < 0.001) and positive surgical margin (13.1% vs 5.7%, p = 0.015). On multivariate Cox regression analyses, variant histology was significantly associated with worse PFS (hazard ratio [HR] 2.23; 95% confidence interval [CI] 1.55-3.21; p < 0.001), CSS (HR 2.67; 95% CI 1.35-5.30; p = 0.005) and OS (HR 2.22; 95% CI 1.27-3.88; p = 0.005). In subgroup analysis, no significant survival gains of adjuvant chemotherapy occurred in patients with variant histology. CONCLUSIONS: Variant histology was associated with adverse pathologic features and poor survival outcomes. Our results suggest that patients with variant histology may require a close follow-up schedule and novel adjuvant therapy other than chemotherapy postoperatively.

The role of preoperative immune cell metrics in renal cell carcinoma with a tumor thrombus.

INTRODUCTION: The objective of this study was to stratify preoperative immune cell counts by cancer specific outcomes in patients with renal cell carcinoma (RCC) and a tumor thrombus after radical nephrectomy with tumor thrombectomy. METHODS: Patients with a diagnosis of RCC with tumor thrombus that underwent radical nephrectomy with thrombectomy across an international consortium of seven institutions were included. Patients who were metastatic at diagnosis and those who received preoperative medical treatment were also included. Retrospective chart review was performed to collect demographic information, past medical history, preoperative lab work, surgical pathology, and follow up data. Neutrophil counts, lymphocyte counts, monocyte counts, neutrophil to lymphocyte ratios (NLR), lymphocyte to monocyte ratios (LMR), and neutrophil to monocyte ratios (NMR) were compared against cancer-specific outcomes using independent samples t-test, Pearson's bivariate correlation, and analysis of variance. RESULTS: One hundred forty-four patients were included in the study, including nine patients who were metastatic at the time of surgery. Absolute lymphocyte count preoperatively was greater in patients who died from RCC compared to those who did not (2 vs 1.4; p < 0.001). Patients with tumor pathology showing perirenal fat invasion had a greater neutrophil count compared to those who did not (7.5 vs 5.5; p = 0.010). Patients with metastatic RCC had a lower LMR compared to those without metastases after surgery (2.5 vs 3.2; p = 0.041). Tumor size, both preoperatively and on gross specimen, had an interaction with multiple immune cell metrics (p < 0.05). CONCLUSIONS: Preoperative immune metrics have clinical utility in predicting cancer-specific outcomes for patients with RCC and a tumor thrombus. Additional study is needed to determine the added value of preoperative serum immune cell data to established prognostic risk calculators for this patient population.

Machine learning models for predicting the onset of chronic kidney disease after surgery in patients with renal cell carcinoma.

BACKGROUND: Patients with renal cell carcinoma (RCC) have an elevated risk of chronic kidney disease (CKD) following nephrectomy. Therefore, continuous monitoring and subsequent interventions are necessary. It is recommended to evaluate renal function postoperatively. Therefore, a tool to predict CKD onset is essential for postoperative follow-up and management. METHODS: We constructed a cohort using data from eight tertiary hospitals from the Korean Renal Cell Carcinoma (KORCC) database. A dataset of 4389 patients with RCC was constructed for analysis from the collected data. Nine machine learning (ML) models were used to classify the occurrence and nonoccurrence of CKD after surgery. The final model was selected based on the area under the receiver operating characteristic (AUROC), and the importance of the variables constituting the model was confirmed using the shapley additive explanation (SHAP) value and Kaplan-Meier survival analyses. RESULTS: The gradient boost algorithm was the most effective among the various ML models tested. The gradient boost model demonstrated superior performance with an AUROC of 0.826. The SHAP value confirmed that preoperative eGFR, albumin level, and tumor size had a significant impact on the occurrence of CKD after surgery. CONCLUSIONS: We developed a model to predict CKD onset after surgery in patients with RCC. This predictive model is a quantitative approach to evaluate post-surgical CKD risk in patients with RCC, facilitating improved prognosis through personalized postoperative care.

Survival pattern of metastatic renal cell carcinoma patients according to WHO/ISUP grade: a long-term multi-institutional study.

The World Health Organization/International Society of Urological Pathology (WHO/ISUP) grading of renal cell carcinoma (RCC) is classified from grade 1-4, regardless of subtype. The National Comprehensive Cancer Network (NCCN) guidelines (2022) state that if there is an adverse pathological feature, such as grade 3 or higher RCC in stage 1 patients, more rigorous follow-up imaging is recommended. However, the RCC guidelines do not provide specific treatment or follow-up policies by tumor grade. Therefore, this study attempted to find out whether tumor grade affects survival rates in patients with metastatic RCC. The Korean Renal Cancer Study Group (KRoCS) database includes 3108 patients diagnosed with metastatic RCC between September 1992 and February 2017, with treatment methods, progression, and survival data collected from 11 tertiary hospitals. To obtain information on survival rates or causes of death, we utilized the Korea National Statistical Office database and institutional medical records. Data were accessed for research purpose on June, 2023. We then reviewed these sources to gather comprehensive and reliable data on the outcomes of our study cohort. This database was retrospectively analyzed, and out of 3108 metastatic RCC patients, 911 had been identified as WHO/ISUP grade. Grades were classified into either a low-grade (WHO/ISUP grade 1-2) or a high-grade group (WHO/ISUP grade 3-4). The patients were then analyzed related to progression and overall survival (OS). In metastatic clear cell RCC patients, the 1-year OS rate was 69.4% and the median OS was 17.0 months (15.5-18.5) followed up to 203.6 months. When comparing the patient groups, 119 low-grade and 873 high-grade cases were identified. No baseline difference was observed between the two groups, except that the high-grade group had a higher ECOG 1 ratio of 50.4% compared with 34.5% for the low-grade group (p = 0.009). There was a significant difference in OS between high-grade and low-grade groups. OS was 16.0 months (14.6-17.4) in the high-grade group and 28.0 months (21.1-34.9) in the low-grade group (p < 0.001). However, there was no difference in progression-free survival (PFS) rates with 9.0 months (8.0-10.0) for the high-grade group and 10.0 months (6.8-13.2) for the low-grade group (p = 0.377) in first-line treatment. In multivariable analysis, WHO/ISUP grade was a risk factor (HR = 1.511[1.135-2.013], p = 0.005) that influenced the OS. In conclusion, WHO/ISUP grade is a major data source that can be used as a ubiquitous marker of metastatic RCC in pre-IO era. Depending on whether the RCC is high or low grade, the follow-up schedule will need to be tailored according to grade, with higher-grade patients needing more active treatment as it can not only affect the OS in the previously known localized/locoregional recurrence but also the metastatic RCC patient.

Retrospective Multicenter Analysis of Prognostic Risk Factors for One Year Recurrence in Patient With Renal Cell Carcinoma After Partial or Radical Nephrectomy: Results of Korean Renal Cancer Study Group (KRoCS) Database.

BACKGROUND: We sought to identify prognostic risk factors for one year recurrence in patient with renal cell carcinoma (RCC) after partial or radical nephrectomy. METHODS: We performed a retrospective study of 1,269 patients with RCC after partial or radical nephrectomy and diagnosed recurrence using Korean Renal Cancer Study Group (KRoCS) database between January 1991 and March 2017. Recurrence-free survival (RFS), and overall survival (OS) were calculated using the Kaplan-Meier method and multivariate Cox regression analysis were performed to evaluate independent prognostic factors for recurrence. RESULTS: The median patient age was 56 years and median follow-up period was 67 months. Multivariable analysis demonstrated BMI greater than or equal to 23 and less than 30 (vs. BMI less than 23, hazard ratio [HR]: 0.707, P = 0.020) reduced recurrence one year postoperatively. Eastern Cooperative Oncology Group performance status (ECOG PS) greater than or equal to 1 (vs. ECOG PS 0, HR: 1.548, P = 0.007), high pathological T stage (pT2 vs. pT1, HR: 2.622, P < 0.001; pT3 vs. pT1, HR: 4.256, P < 0.001; pT4 vs. pT1, HR: 4.558, P < 0.001), and tumor necrosis (vs. no tumor necrosis, HR: 2.822, P < 0.001) were independent predictive factors for early recurrence within one year in patients with RCC. Statistically significant differences on RFS and OS were found among pathological T stages (pT2 vs. pT1; pT3 vs. pT1; pT4 vs. pT1, all P < 0.001). CONCLUSION: This large multicenter study demonstrated ECOG PS greater than or equal to 1, high pathological T stage, tumor necrosis and BMI less than 23 were significant prognostic risk factors of early recurrence within one year in patients with RCC who underwent nephrectomy.

Partial gland ablation using high-intensity focused ultrasound versus robot-assisted radical prostatectomy: a propensity score-matched study.

Background: We compared the clinical outcomes of robot-assisted radical prostatectomy (RARP) and partial gland ablation (PGA) using high-intensity focused ultrasound (HIFU) in localized prostate cancer. Methods: We analyzed 3,859 patients who had undergone RARP and PGA using HIFU. According to the propensity score for each treatment, 137 patients after PGA were matched to 3,722 patients after RARP at a 1:4 ratio using the nearest neighbor method. Results: The matched cohort comprised 685 subjects (RARP, 548; PGA, 137), with a median follow-up period of 22 months. Treatment failures were identified in 13.9% and 9.1% of patients in the PGA and RARP groups, respectively, after a median follow-up of 36 months postoperatively. Kaplan-Meier analyses revealed significantly longer failure-free (P < 0.001) and salvage-free survival (P = 0.003) in the RARP group than in the PGA group. There was no significant difference in the postoperative urinary symptom score (P = 0.748), but the postoperative erectile function score was significantly higher in the PGA group (P < 0.001). The rate of urinary incontinence (any pad) was significantly lower in the PGA group than that in the RARP group (P < 0.001). Postoperative complications were more frequent in the PGA group (P = 0.003); however, there was no significant difference in high-grade complications (≥3) (P = 0.467). Conclusion: PGA using HIFU showed statistically inferior oncological outcomes compared with RARP for failure-free survival and salvage-free survival. However, functional outcomes regarding postoperative incontinence and erectile dysfunction were more favorable in the PGA group.

Computer tomography-based shape of tumor contour and texture of tumor heterogeneity are independent prognostic indicators for clinical T1b-T2 renal cell carcinoma.

PURPOSE: To evaluate association between computer tomography (CT)-based features of renal cell carcinoma (RCC) and survival outcomes. METHODS: Data of 958 patients with clinical T1b-T2 RCC who underwent partial/radical nephrectomy from June 2003 to March 2022 were retrospectively evaluated. CT images of patients were reviewed by two radiologists for texture analysis of tumor heterogeneity and shape analysis of tumor contour. Patients were divided into three groups according to patterns of CT-based features: (1) favorable feature group (n = 117); (2) intermediate feature group (n = 606); and (3) unfavorable feature group (n = 235). Kaplan-Meier survival analysis and multivariate Cox regression analysis were performed to evaluate overall survival (OS), cancer-specific survival (CSS), and recurrence-free survival (RFS). RESULTS: RCCs with unfavorable CT-based feature showed larger size on CT, higher nuclear grade, higher rate of histologic necrosis, and higher rate of capsular invasion than those in the other two groups (all p < 0.001). Unfavorable feature was associated with poorer OS (p = 0.001), CSS (p < 0.001), and RFS (p < 0.001) on Kaplan-Meier analysis. In multivariate analysis, intermediate and unfavorable features were independent predictors for recurrence (hazard ratio [HR] 2.51, 95% confidence interval [CI] 1.09-5.79, p = 0.031 and HR 3.71, 95% CI 1.58-8.73, p = 0.003, respectively), but not for overall death or RCC-specific death. CONCLUSIONS: A combination of irregular tumor contour feature with heterogeneous tumor texture feature on CT is associated with poor RFS in clinical T1b-T2 RCC preoperatively.

Interpretation of the effects of anthropogenic chlorine on nitrate formation over northeast Asia during KORUS-AQ 2016.

The Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model, implemented with anthropogenic chlorine (Cl) emissions, was evaluated against ground and NASA DC-8 aircraft measurements during the Korea-United States Air Quality (KORUS-AQ) 2016 campaign. The latest anthropogenic Cl emissions, including gaseous HCl and particulate chloride (pCl-) emissions from the Anthropogenic Chlorine Emissions Inventory of China (ACEIC-2014) (over China) and a global emissions inventory (Zhang et al., 2022) (over outer China), were used to examine the impacts of Cl emissions and the role of nitryl chloride (ClNO2) chemistry in N2O5 heterogeneous reactions on secondary nitrate (NO3-) formation across the Korean Peninsula. The model results against aircraft measurements clearly showed significant Cl- underestimations due mainly to the high gas-particle (G/P) partitioning ratios at aircraft measurement altitudes such as 700-850 hPa, but the ClNO2 simulations were reasonable. Several simulations of CMAQ-based sensitivity experiments against ground measurements indicated that although addition of Cl emission did not significantly alter NO3- formation, the activated ClNO2 chemistry with Cl emissions showed the best model performance with the reduced normalized mean bias (NMB) of 18.7 % compared to a value of 21.1 % for the Cl emissions-free case. In our model evaluation, ClNO2 accumulated during the night but quickly produced Cl radical due to ClNO2 photolysis at sunrise, which modulated other oxidation radicals (e.g., ozone [O3] and hydrogen oxide radicals [HOx]) in the early morning. In the morning hours (0800-1000 LST), the HOx were the dominant oxidants, contributing 86.6 % of the total oxidation capacity (sum of major oxidants such as O3 and HOx species), while oxidability was enhanced by up to ∼6.4 % (increase in 1 h HOx average of 2.89 × 106 molecules·cm-3) in the early morning mainly due to the changes in OH (+7.2 %), hydroperoxyl radical (HO2)(+10.0 %), and O3 (+4.2 %) over the Seoul Metropolitan Area, during the KORUS-AQ campaign. Our results improve understanding of the atmospheric changes in the PM2.5 formation pathway caused by ClNO2 chemistry and Cl emissions over northeast Asia.

Machine learning based prediction for oncologic outcomes of renal cell carcinoma after surgery using Korean Renal Cell Carcinoma (KORCC) database.

We developed a novel prediction model for recurrence and survival in patients with localized renal cell carcinoma (RCC) after surgery and a novel statistical method of machine learning (ML) to improve accuracy in predicting outcomes using a large Asian nationwide dataset, updated KOrean Renal Cell Carcinoma (KORCC) database that covered data for a total of 10,068 patients who had received surgery for RCC. After data pre-processing, feature selection was performed with an elastic net. Nine variables for recurrence and 13 variables for survival were extracted from 206 variables. Synthetic minority oversampling technique (SMOTE) was used for the training data set to solve the imbalance problem. We applied the most of existing ML algorithms introduced so far to evaluate the performance. We also performed subgroup analysis according to the histologic type. Diagnostic performances of all prediction models achieved high accuracy (range, 0.77-0.94) and F1-score (range, 0.77-0.97) in all tested metrics. In an external validation set, high accuracy and F1-score were well maintained in both recurrence and survival. In subgroup analysis of both clear and non-clear cell type RCC group, we also found a good prediction performance.

Optimal management of renal cell carcinoma in octogenarians: Retrospective analysis using updated Korean Renal Cell Carcinoma (KORCC) database.

BACKGROUND: There is few of optimal management guideline in elderly patients with renal cell carcinoma (RCC). To compare the survival outcomes of octogenarian RCC group and younger RCC group after surgery using nationwide multi-institutional database. METHODS: A total of 10,068 patients who underwent surgery for RCC were included in the current retrospective, multi-institutional study. A propensity score matching (PSM) analysis was conducted to control other confounding factors in analyzing survival outcomes of octogenarian and younger group RCCs. Kaplan-Meier curve analysis to calculate the survival estimates for cancer-specific survival (CSS) and overall survival (OS), and multivariate Cox-proportional hazard regression analyses to evaluate the significant variables associated with the survival outcomes were also performed. RESULTS: Both groups were well-balanced in all baseline characteristics. In a total cohort, Kaplan-Meier survival analysis showed a significantly decreased 5-year and 8-year CSS and OS in the octogenarian group compared with the younger group. However, in a PSM cohort, no significant differences were evident between the two groups in terms of CSS (5-year, 87.3% vs. 87.0%; 8-year, 82.2% vs. 78.9%, respectively, log-rank test, p = 0.964). In addition, age ≥ 80 years (HR, 1.199; 95% CI, 0.497-2.896, p = 0.686) was not a significant prognostic factor of CSS in a PSM cohort. CONCLUSIONS: The octogenarian RCC group after surgery had comparable survival outcomes compared with younger group after PSM analysis. For the life expectancy of octogenarian is getting longer, active treatment is considerable in patients with good performance status.

Polygenic risk score for tumor aggressiveness and early-onset prostate cancer in Asians.

We attempted to assess the performance of an ethnic-specific polygenic risk score (PRS) designed from a Korean population to predict aggressive prostate cancer (PCa) and early-onset (age < 60). A PRS score comprised of 22 SNPs was computed in 3695 patients gathered from one of 4 tertiary centers in Korea. Males with biopsy or radical prostatectomy-proven PCa were included for analysis, collecting additional clinical parameters such as age, BMI, PSA, Gleason Group (GG), and staging. Patients were divided into 4 groups of PRS quartiles. Intergroup differences were assessed, as well as risk ratio and predictive performance based on GG using logistic regression analysis and AUC. No significant intergroup differences were observed for BMI, PSA, and rate of ≥ T3a tumors on pathology. Rate of GG ≥ 2, GG ≥ 3, and GG ≥ 4 showed a significant pattern of increase by PRS quartile (p < 0.001, < 0.001, and 0.039, respectively). With the lowest PRS quartile as reference, higher PRS groups showed sequentially escalating risk for GG ≥ 2 and GG ≥ 3 pathology, with a 4.6-fold rise in GG ≥ 2 (p < 0.001) and 2.0-fold rise in GG ≥ 3 (p < 0.001) for the highest PRS quartiles. Combining PRS with PSA improved prediction of early onset csPCa (AUC 0.759) compared to PRS (AUC 0.627) and PSA alone (AUC 0.736). To conclude, an ethnic-specific PRS was found to predict susceptibility of aggressive PCa in addition to improving detection of csPCa when combined with PSA in early onset populations. PRS may have a role as a risk-stratification model in actual practice. Large scale, multi-ethnic trials are required to validate our results.

Establishment of Prospective Registry of Active Surveillance for Prostate Cancer: The Korean Urological Oncology Society Database.

PURPOSE: To establish a prospective registry for the active surveillance (AS) of prostate cancer (PC) using the Korean Urological Oncology Society (KUOS) database and to present interim analysis. MATERIALS AND METHODS: The KUOS registry of AS for PC (KUOS-AS-PC) was organized in May 2019 and comprises multiple institutions nationwide. The eligibility criteria were as follows: patients with (1) pathologically proven PC; (2) pre-biopsy prostate-specific antigen (PSA) ≤20 ng/mL; (3) International Society of Urological Pathology (ISUP) grade 1 or 2 (no cribriform pattern 4); (4) clinical T stage ≤T2c; (5) positive core ratio ≤50%; and (6) maximal cancer involvement in the core ≤50%. Detailed longitudinal clinical information, including multi-parametric magnetic resonance imaging and disease-specific outcomes, was recorded. RESULTS: From May 2019 to June 2021, 296 patients were enrolled, and 284 were analyzed. The mean±standard deviation (SD) age at enrollment was 68.7±8.2 years. The median follow-up period was 11.2 months (5.9-16.8 mo). Majority of patients had pre-biopsy PSA ≤10 ng/mL (91.2%), PSA density <0.2 ng/mL² (79.7%), ISUP grade group 1 (94.4%), single positive core (65.7%), maximal cancer involvement in the core ≤20% (78.1%), and clinical T stage of T1c or lower (72.9%). Fifty-two (18.3%) discontinued AS for various reasons. Interventions included radical prostatectomy (80.8%), transurethral prostatectomy (5.8%), primary androgen deprivation therapy (5.8%), radiation (5.8%), and focal therapy (1.9%). The mean±SD time to intervention was 8.9±5.2 months. The reasons for discontinuation included pathologic reclassification (59.6%), patient preference (25.0%), and radiologic reclassification (9.6%). Two (4.8%) patients with pathologic Gleason score upgraded to ISUP grade group 4, no biochemical recurrence. CONCLUSIONS: The KUOS established a successful prospective database of PC patients undergoing AS in Korea, named the KUOS-AS-PC registry.

Possibilities and limitations of using low biomass samples for urologic disease and microbiome research.

With the dogma of sterile urine no longer held as truth, numerous studies have implicated distinct changes in microbial diversity and composition to diseased subgroups in both benign and malignant urological diseases, ranging from overactive bladder to bladder and prostate cancer. Further facilitated by novel and effective techniques of urine culture and sequencing, analysis of the genitourinary microbiome holds high potential to identify biomarkers for disease and prognosis. However, the low biomass of samples included in microbiome studies of the urinary tract challenge researchers to draw definitive conclusions, confounded by technical and procedural considerations that must be addressed. Lack of samples and adequate true negative controls can lead to overestimation of microbial influence with clinical relevance. As such, results from currently available studies and assessment of their limitations required a thorough understanding. The purpose of this narrative review was to summarize notable microbiome studies in the field of urology with a focus on significant findings and limitations of study design. Methodological considerations in future research are also discussed.

Clinical benefits of retrograde bladder filling method prior to catheter removal after TURP for BPH: A prospective randomized trial.

PURPOSE: To evaluate possible benefits and clinical feasibility of retrograde bladder filling method prior to intra-vesical catheter removal after transurethral prostatectomy (TURP) for benign prostatic hyperplasia (BPH). MATERIALS AND METHODS: Male patients undergoing TURP for BPH from January 2019 to October 2019 were randomized in a 1:1 ratio into either retrograde filling (RF) or spontaneous voiding (SV) methods at a single institution to determine safety and efficacy of RF (NCT04309032), with surgeons blinded to allocation. Perioperative outcomes including postoperative complications were compared between two groups. Clinician/patients' satisfaction level which was evaluated with postoperative questionnaires were also compared. RESULTS: A total of 56 patients were randomized into two groups and 56 were included in final analysis (28 men in RF group, 26 in SV group). No significant differences in baseline characteristics including age, prostate volume, or perioperative uroflowmetry were observed. However, RF significantly facilitated time to void (67.0±63.2 vs. 144.0±78.7 min; p<0.001) and time to discharge (168.4±57.2 vs. 218.9±106.9 min; p=0.046). Immediate postoperative complications were comparable in both methods with no significant difference. Overall patient and medical staff satisfaction showed tolerable and similar response by either procedure. CONCLUSIONS: RF method for intra-vesical catheter removal is a safe and satisfactory method that can facilitate early voiding detection and shorten the time to discharge. Further trials are required to further validate our results.

Diagnostic accuracy of F-18-Fluorocholine PET/CT and multiparametric MRI for prostate cancer.

Background: Positron emission tomography (PET) using different positron-emitting radiopharmaceuticals has emerged as a promising new metabolic diagnostic tool for the evaluation of a variety of malignant diseases. Thus, we investigated the diagnostic efficacy of F-18-Fluorocholine positron emission tomography/computed tomography (PET/CT) and multiparametric magnetic resonance imaging (mpMRI) for the detection and localization of tumors within the prostate with the correlating histopathology as the standard of reference. Methods: Forty patients with histologically proven prostate cancer underwent both F-18-Fluorocholine PET/CT and mpMRI before robot-assisted laparoscopic radical prostatectomy (RARP). The maximum standard uptake values and the tumor-to-background ratio were measured on a sextant basis. In brief, the sextants were defined as right apex, right middle, right base, left apex, left middle, and left base. For each tumor region, the correlation of the tumor localization based on the sextant in both F-18-Fluorocholine PET/CT and mpMRI scans with the histopathological results was determined. Results: The correlation between both imaging modalities and RARP pathology representing (1) all cancer and (2) clinically significant cancer defined as a ≥ International Society of Urological Pathology grade of 2 showed that the sensitivity and the area under the curve (AUC) were higher for mpMRI than for F-18-Fluorocholine PET/CT. In contrast, F-18-Fluorocholine PET/CT had relatively higher specificity than mpMRI. Importantly, we found a very high AUC value of over 0.8 in both imaging modalities. Conclusion: mpMRI had results superior to F-18-Fluorocholine PET/CT in assessing intraprostatic tumor localization. However, F-18-Fluorocholine PET/CT showed superiority in terms of specificity. Thus, using both modalities in conjunction could provide better treatment planning.

The association between prostatitis and risk of prostate cancer: a National Health Insurance Database study.

PURPOSE: Inflammation is thought to affect the development of prostate cancer (PCa). By retrospectively investigating the database of the National Health Insurance Service, this study attempted to perform a relevant analysis of patients with prostatitis and PCa. METHODS: Participants were aged ≥ 50 years. Patients diagnosed with prostatitis between 2010 and 2013 and matched controls were followed up until 2019. We selected controls with matched propensity scores for age, diabetes, hypertension, and the Charlson comorbidity index. Multivariate Cox regression analysis was conducted to determine the hazard ratio (HR) and 95% confidence interval (CI) of the association between prostatitis and PCa. The HR for PCa according to the presence of prostatitis was classified as acute, chronic, or other prostatitis. RESULTS: A total of 746,176 patients from each group were analyzed. The incidence of PCa was significantly higher in the group with prostatitis (1.8% vs 0.6%, p < 0.001). The HR for PCa was significantly higher in patients with prostatitis (HR 2.99; 95% CI 2.89-3.09, p < 0.001). The HR for PCa was significantly higher in acute prostatitis than in chronic prostatitis (3.82; 95% CI 3.58-4.08; p < 0.001; HR 2.77; 95% CI 2.67-2.87, p < 0.001). The incidence of all-cause death in patients diagnosed PCa was significantly lower in prostatitis group (HR 0.58, 95% CI 0.53-0.63, p < 0.001). CONCLUSION: Prostatitis is associated with an increased incidence of PCa. Acute prostatitis is associated with higher risk of PCa than chronic prostatitis. Clinicians should inform patients with prostatitis that they may have an increased risk of diagnosing PCa, and follow-up is needed.

Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma.

BACKGROUND: Renal cell carcinoma is characterized by a late recurrence that occurs 5 years after surgery; hence, continuous monitoring and follow-up is necessary. Prognosis of late recurrence of renal cell carcinoma can only be improved if it is detected early and treated appropriately. Therefore, tools for rapid and accurate renal cell carcinoma prediction are essential. METHODS: This study aimed to develop a prediction model for late recurrence after surgery in patients with renal cell carcinoma that can be used as a clinical decision support system for the early detection of late recurrence. We used the KOrean Renal Cell Carcinoma database that contains large-scale cohort data of patients with renal cell carcinoma in Korea. From the collected data, we constructed a dataset of 2956 patients for the analysis. Late recurrence and non-recurrence were classified by applying eight machine learning models, and model performance was evaluated using the area under the receiver operating characteristic curve. RESULTS: Of the eight models, the AdaBoost model showed the highest performance. The developed algorithm showed a sensitivity of 0.673, specificity of 0.807, accuracy of 0.799, area under the receiver operating characteristic curve of 0.740, and F1-score of 0.609. CONCLUSIONS: To the best of our knowledge, we developed the first algorithm to predict the probability of a late recurrence 5 years after surgery. This algorithm may be used by clinicians to identify patients at high risk of late recurrence that require long-term follow-up and to establish patient-specific treatment strategies.

Multiple primary cancers in men with sporadic or familial prostate cancer: Its clinical implications.

OBJECTIVE: To evaluate the risk of concordant cancers in patients with prostate cancer (CaP) and examine whether this risk differed according to family history of CaP. MATERIALS AND METHODS: We examined 1,102 patients with CaP , having prospectively acquired pedigrees, and analyzed information regarding multiple primary cancers. The prevalence of concordant cancers was assessed with respect to the family history of CaP . First-degree familial CaP was defined as a positive history of CaP in first-degree relatives (parents, siblings, and offspring). Odds ratios for each concordant cancer in men with first-degree familial CaP were estimated. Clinical characteristics were compared between men with and without concordant cancers. RESULTS: The prevalence of multiple primary cancers in sporadic PCa was 12.0%, similar to that of first-degree familial CaP (13.5%, P = 0.698). Gastrointestinal cancer was the most common concordant cancer (3.6%), followed by colorectal (2.9%), lung (1.5%), urothelial (1.3%), kidney (1.1%), and other cancers. Colorectal cancer was more frequent in first-degree familial CaP than in sporadic disease (6.8 vs. 2.7%, P = 0.045). However, the rates of other concordant cancers were similar between the 2 groups (P range, 0.242-0.963). Compared with sporadic disease, the age-adjusted odds ratio for concordant colorectal cancer in first-degree familial CaP was 2.930 (95% confidence interval, 1.082-7.929). Patients with concordant colorectal cancer had fewer (2.8 vs. 3.9 cores, P = 0.041) and a lower percentage of (23.5 vs. 33.1%, P = 0.030) positive biopsy cores than CaP only patients. CONCLUSIONS: A family history of CaP was significantly associated with a risk of concordant colorectal cancer. These findings imply that some CaP shares a genetic pathogenesis with colorectal cancer.

A smart, practical, deep learning-based clinical decision support tool for patients in the prostate-specific antigen gray zone: model development and validation.

OBJECTIVE: Despite efforts to improve screening and early detection of prostate cancer (PC), no available biomarker has shown acceptable performance in patients with prostate-specific antigen (PSA) gray zones. We aimed to develop a deep learning-based prediction model with minimized parameters and missing value handling algorithms for PC and clinically significant PC (CSPC). MATERIALS AND METHODS: We retrospectively analyzed data from 18 824 prostate biopsies collected between March 2003 and December 2020 from 2 databases, resulting in 12 739 cases in the PSA gray zone of 2.0-10.0 ng/mL. Dense neural network (DNN) and extreme gradient boosting (XGBoost) models for PC and CSPC were developed with 5-fold cross-validation. The area under the curve of the receiver operating characteristic (AUROC) was compared with that of serum PSA, PSA density, free PSA (fPSA) portion, and prostate health index (PHI). RESULTS: The AUROC values in the DNN model with the imputation of missing values were 0.739 and 0.708 (PC) and 0.769 and 0.742 (CSPC) in internal and external validation, whereas those of the non-imputed dataset were 0.740 and 0.771 (PC) and 0.807 and 0.771 (CSPC), respectively. The performance of the DNN model was like that of the XGBoost model, but better than all tested clinical biomarkers for both PC and CSPC. The developed DNN model outperformed PHI, serum PSA, and percent-fPSA with or without missing value imputation. DISCUSSION: DNN models for missing value imputation can be used to predict PC and CSPC. Further validation in real-life scenarios are need to recommend for actual implementation, but the results from our study support the increasing role of deep learning analytics in the clinical setting. CONCLUSIONS: A deep learning model for PC and CSPC in PSA gray zones using minimal, routinely used clinical parameter variables and data imputation of missing values was successfully developed and validated.