Comparation of intraureteral stent and conventional stent at different stages: a systematic review with meta-analysis.

INTRODUCTION: Stent related symptom (SRS) is the most common adverse effect of ureteral stenting. In recent years, many efforts have been made to develope modified ureteral stents to ameliorate SRS. It has been reported that intraureteral stents have the potential to improve the tail end adverse effect of the bladder and alleviate SRS. However, there still lack of evidence for the efficacy and the safety of clinically applying intraureteral stents. The aim of this work is to investigate the efficacy and safety of intraureteral stents. EVIDENCE ACQUISITION: A systematic review was performed by using the PubMed, Web of Science, Medline, Embase, and Cochrane library. The studies published before February 2023 were included. The study selection was following the guideline from Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). The searching strategy was: "Pigtail suture stent" OR "Intra-ureteric stent" OR "Suture Stent" OR "Intraureteral stent" AND "Ureteroscopy" OR "Urinary calculi" OR "Stent-related symptoms" OR "Lower urinary tract symptoms". The data from randomized clinical trials which meet the selection criteria were extracted. Revman 5.4 was employed to proceed the meta-analysis. EVIDENCE SYNTHESIS: A total of six randomized clinical trials of intraureteral stents were included in this systematic review and meta-analysis. According to the different investigation time, the results could be divided into four stages: early-stage, middle-stage, late-stage, and long-term evaluation. Urinary symptoms, pain score, and general health were significantly improved in intraureteral stents group at middle stage. For late-stage, intraureteral stent achieved better outcomes in urinary symptoms index, VAS score, quality of life, general health, and pain score. However, for early-stage and long-term evaluation, there was no significant difference between two groups. CONCLUSIONS: This systematic review and meta-analysis reveal that regardless of the stage of treatment, the efficacy and safety of intraureteral stent are no worse than that of conventional stent. During 7-14 days postoperation, which is the most commonly time for clinically using ureteral stent, most of the outcomes of intraureteral stent are better than those of conventional stent. Hence, it is confirmed that intraureteral stent is worth for more clinical study and application.

Combination therapy for high-volume versus low-volume metastatic hormone-sensitive prostate cancer: A systematic review and network meta-analysis.

Purpose: To conduct a systematic review and network meta-analysis (NMA) to compare the efficacy of currently available combination therapies in patients with metastatic hormone-sensitive prostate cancer (mHSPC). Methods: Qualified publications were searched in the PubMed, Embase, and Cochrane CENTRAL databases. Overall survival (OS) and radiographic progression-free survival (rPFS) were indirectly compared and assessed using NMA and the surface under the cumulative ranking curve, respectively. Adverse events (AEs) were also compared. Results: Eighteen publications from 12 trials were analyzed in the NMA. In the overall population, triplet therapy was ranked first for OS (hazard ratio [HR]: 0.57, 95% credible interval [CrI]: 0.48-0.67) and rPFS (HR: 0.33, 95% CrI:0.26-0.41) compared with androgen deprivation therapy (ADT) with or without standard non-steroidal antiandrogen. In high-volume mHSPC, triplet therapy was also ranked first in OS (HR, 0.57; 95% CrI:0.44-0.75) and rPFS(HR, 0.29; 95% CrI: 0.23-0.37). Specifically, abiraterone triplet therapy was ranked first in OS (HR, 0.52; 95% CrI:0.38-0.72) and rPFS (HR, 0.28; 95% CrI:0.21-0.38) among all therapies. ADT plus rezvilutamide was ranked first among doublet therapies (OS: HR, 0.58; 95% CrI:0.44-0.77; rPFS: HR, 0.44; 95% CrI:0.33-0.58). In low-volume mHSPC, doublet and triplet therapies were ranked first in OS (HR:0.68, 95% CrI:0.58-0.80) and rPFS (HR:0.37, 95% CrI:0.25-0.55), respectively. ADT plus apalutamide was ranked first in OS among all therapies (HR:0.53, 95% CrI:0.35-0.79), whereas enzalutamide triplet therapy was ranked first in rPFS (HR:0.27, 95% CrI:0.15-0.51). ADT plus rezvilutamide showed a relatively lower incidence of AE among all therapies (OR:1.00, 95% CrI:0.31-3.15), and a lower risk of specific AEs among doublet therapies, particularly regarding seizure (OR, 0.29; 95% CrI:0.01-8.18) and fatigue (OR, 0.96; 95% CrI:0.63-1.46). Docetaxel-based doublet or triplet therapies significantly increased the risk of any AEs or grade ≥3 AEs. Conclusion: Triplet therapy was the best treatment option for the overall population. In high-volume mHSPC, triplet therapy and ADT plus rezvilutamide had the greatest potential to benefit patients. Patients with low-volume mHSPC were most likely to benefit from ADT plus androgen receptor-targeted agents. Triplet therapy was associated with a higher risk of AEs than the other therapies. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022375347, identifier PROSPERO:CRD42022375347.

Urinary incontinence rehabilitation of after radical prostatectomy: a systematic review and network meta-analysis.

Purpose: The aim of this study is to provide treatment for patients with urinary incontinence at different periods after radical prostatectomy. Methods: The PubMed, Embase, Cochrane, and Web of Science were searched for all literature on the effectiveness on urinary control after radical prostate cancer between the date of database creation and 15 November 2023 and performed a quality assessment. A network meta-analysis was performed using RevMan 5.3 and Stata 17.0 software and evaluated using the surface under the cumulative ranking curve. Results: The results of the network meta-analysis showed that pelvic floor muscle therapy including biofeedback with professional therapist-guided treatment demonstrated better results at 1 month to 6 months; electrical stimulation, biofeedback, and professional therapist guidance may be more effective at 3 months of treatment; professional therapist-guided recovery may be less effective at 6 months of treatment; and combined therapy demonstrated better results at 1 year of treatment. During the course of treatment, biofeedback with professional therapist-guided treatment may have significant therapeutic effects in the short term after surgery, but, in the long term, the combination of multiple treatments (pelvic floor muscle training+ routine care + biofeedback + professional therapist-guided treatment + electrical nerve stimulation therapy) may address cases of urinary incontinence that remain unrecovered long after surgery. Conclusion: In general, all treatment methods improve the different stages of functional recovery of the pelvic floor muscles. However, in the long term, there are no significant differences between the treatments. Given the cost-effectiveness, pelvic floor muscle training + routine care + biofeedback + professional therapist-guided treatment + electrical nerve stimulation therapy within 3 months and pelvic floor muscle + routine care after 3 months may be a more economical option to treat urinary incontinence. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=331797, identifier CRD42022331797.

Systemic triplet therapy for metastatic hormone-sensitive prostate cancer: A systematic review and network meta-analysis.

Purpose: To perform a systematic review and network meta-analysis to compare the efficacy and safety of currently available docetaxel-based systemic triplet therapies for metastatic hormone-sensitive prostate cancer (mHSPC). Methods: We searched for eligible publications in PubMed, Embase, and Cochrane CENTRAL. Improvements in overall survival (OS) and radiographic progression-free time (rPFS) were compared indirectly using network meta-analysis and evaluated using the surface under the cumulative ranking curve (SUCRA). Other secondary endpoints, such as time to castration-resistant prostate cancer and/or adverse events (AEs), were also compared and evaluated. Results: Five trials were selected and analyzed using a network meta-analysis. Compared to androgen deprivation therapy (ADT) plus docetaxel, darolutamide (hazard ratio [HR]: 0.68, 95% credible interval [CrI]: 0.57-0.80) and abiraterone (HR: 0.75, 95% CrI: 0.59-0.95) triplet therapy had significantly longer OS, and darolutamide triplet therapy was the first treatment ranked. Abiraterone (HR: 0.49, 95% CrI: 0.39-0.61) and enzalutamide (HR: 0.52, 95% CrI: 0.30-0.89) had significantly better rPFS than ADT plus docetaxel; however, all three therapies, including abiraterone, apalutamide, and enzalutamide, were the best options with a similar SUCRA. At most secondary endpoints, systemic triplet therapy was superior to ADT plus docetaxel. The risk of any AEs in darolutamide or abiraterone triplet therapy was comparable with ADT plus docetaxel (odds ratio [OR]: 2.53, 95% credible interval [CrI]: 0.68-12.63; OR: 1.07, 95% CrI: 0.03-36.25). Abiraterone triplet therapy had an increased risk of grade≥3 AEs (OR: 1.56, 95% CrI: 1.15-2.11). Conclusion: Systemic triplet therapy was more effective than ADT plus docetaxel for mHSPC. Of the triplet therapy regimens, darolutamide ranked first in terms of improved OS. Abiraterone and enzalutamide triplet ranked first in terms of rFPS, however, it did not confer a statistically difference among all triplet regimens. The overall risk of AEs was comparable. More studies are required for current and potential combinations of systemic triplet therapy.

Machine Learning-Based Models Enhance the Prediction of Prostate Cancer.

Purpose: PSA is currently the most commonly used screening indicator for prostate cancer. However, it has limited specificity for the diagnosis of prostate cancer. We aim to construct machine learning-based models and enhance the prediction of prostate cancer. Methods: The data of 551 patients who underwent prostate biopsy were retrospectively retrieved and divided into training and test datasets in a 3:1 ratio. We constructed five PCa prediction models with four supervised machine learning algorithms, including tPSA univariate logistic regression (LR), multivariate LR, decision tree (DT), random forest (RF), and support vector machine (SVM). The five prediction models were compared based on model performance metrics, such as the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, calibration curve, and clinical decision curve analysis (DCA). Results: All five models had good calibration in the training dataset. In the training dataset, the RF, DT, and multivariate LR models showed better discrimination, with AUCs of 1.0, 0.922 and 0.91, respectively, than the tPSA univariate LR and SVM models. In the test dataset, the multivariate LR model exhibited the best discrimination (AUC=0.918). The multivariate LR model and SVM model had better extrapolation and generalizability, with little change in performance between the training and test datasets. Compared with the DCA curves of the tPSA LR model, the other four models exhibited better net clinical benefits. Conclusion: The results of the current retrospective study suggest that machine learning techniques can predict prostate cancer with significantly better AUC, accuracy, and net clinical benefits.