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This umbrella review aimed to summarize and provide a general evaluation of the effectiveness of current treatments for male infertility and assess the quality of evidence and possible biases. An umbrella review of systematic reviews and meta-analyses available in PubMed, Web of Science, and Scopus, covering studies published up to October 2023, was conducted. Sperm concentration, morphology, and motility were used as endpoints to evaluate the effectiveness of the treatments. Of 2998 studies, 18 published meta-analyses were extracted, yielding 90 summary effects on sperm concentration (n = 36), sperm morphology (n = 26), and sperm motility (n = 28) on 28 interventions. None of the meta-analyses were classified as having low methodological quality, whereas 12 (66.7%) and 6 (33.3%) had high and moderate quality, respectively. Of the 90 summary effects, none were rated high-evidence quality, whereas 53.3% (n = 48), 25.6% (n = 23), and 21.1% (n = 19) were rated moderate, low, and very low, respectively. Significant improvements in sperm concentration, morphology, and motility were observed with pharmacological interventions (N-acetyl-cysteine, antioxidant therapy, aromatase inhibitors, selective estrogen receptor modulators, hormones, supplements, and alpha-lipoic acid) and nonpharmacological interventions (varicocele repair and redo varicocelectomy). In addition, vitamin supplementation had no significant positive effects on sperm concentration, motility, or morphology. Treatments for male infertility are increasingly diverse; however, the current evidence is poor because of the limited number of patients. Further well-designed studies on single treatment and high-quality meta-analysis of intertreatment comparisons are recommended.

Abstract Robot-assisted surgery has evolved into a crucial treatment for prostate cancer (PCa). However, from its appearance to today, brain-computer interface, virtual reality, and metaverse have revolutionized the field of robot-assisted surgery for PCa, presenting both opportunities and challenges. Especially in the context of contemporary big data and precision medicine, facing the heterogeneity of PCa and the complexity of clinical problems, it still needs to be continuously upgraded and improved. Keeping this in mind, this article summarized the 5 stages of the historical development of robot-assisted surgery for PCa, encompassing the stages of emergence, promotion, development, maturity, and intelligence. Initially, safety concerns were paramount, but subsequent research and engineering advancements have focused on enhancing device efficacy, surgical technology, and achieving precise multi modal treatment. The dominance of da Vinci robot-assisted surgical system has seen this evolution intimately tied to its successive versions. In the future, robot-assisted surgery for PCa will move towards intelligence, promising improved patient outcomes and personalized therapy, alongside formidable challenges. To guide future development, we propose 10 significant prospects spanning clinical, research, engineering, materials, social, and economic domains, envisioning a future era of artificial intelligence in the surgical treatment of PCa.

We attempted to perform risk categories based on the free/total prostate-specific antigen ratio (%fPSA), prostate-specific antigen (PSA) density (PSAD, in ng ml−2), and multiparametric magnetic resonance imaging (mpMRI) step by step, with the goal of determining the best clinical diagnostic strategy to avoid unnecessary tests and prostate biopsy (PBx) in biopsy-naïve men with PSA levels ranging from 4 ng ml−1 to 10 ng ml−1. We included 439 patients who had mpMRI and PBx between August 2018 and July 2021 (West China Hospital, Chengdu, China). To detect clinically significant prostate cancer (csPCa) on PBx, receiver-operating characteristic (ROC) curves and their respective area under the curve were calculated. Based on %fPSA, PSAD, and Prostate Imaging-Reporting and Data System (PI-RADS) scores, the negative predictive value (NPV) and positive predictive value (PPV) were calculated sequentially. The optimal %fPSA threshold was determined to be 0.16, and the optimal PSAD threshold was 0.12 for %fPSA ≥0.16 and 0.23 for %fPSA

This study aimed to assess the role of prostate-specific antigen density (PSAD) and negative multiparametric magnetic resonance imaging (mpMRI) in predicting prostate cancer for biopsy-naïve men based on a large cohort of the Chinese population. From a prostate biopsy database between March 2017 and July 2021, we retrospectively identified 240 biopsy-naïve patients with negative prebiopsy mpMRI (Prostate Imaging Reporting and Data System version 2 [PI-RADS v2] score

Prostate cancer (PCa) is the second-most common cancer among men. Both active surveillance or watchful waiting (AS/WW) and focal laser ablation (FLA) can avoid the complications caused by radical treatment. How to make the choice between these options in clinical practice needs further study. Therefore, this study aims to compare and analyze their effects based on overall survival (OS) and cancer-specific survival (CSS) to obtain better long-term benefits. We included patients with low-risk PCa from the Surveillance Epidemiology and End Results database of 2010–2016. Multivariate Cox proportional hazard analyses were conducted for OS and CSS in the two groups. To eliminate bias, this study applied a series of sensitivity analyses. Moreover, Kaplan–Meier curves were plotted to obtain survival status. A total of 18 841 patients with low-risk PCa were included, with a median of 36-month follow-up. According to the multivariate Cox proportional hazard regression, the FLA group presented inferior survival benefits in OS than the AS/WW group (hazard ratio [HR]: 2.13, 95% confidence interval [CI]: 1.37–3.33, P < 0.05). After adjusting for confounders, the result persisted (HR: 1.69, 95% CI: 1.02–2.81, P < 0.05). According to the results of the sensitivity analysis, the inverse probability of the treatment weighing model indicated the same result in OS. In conclusion, AS/WW and FLA have the advantage of fewer side effects and the benefit of avoiding overtreatment compared with standard treatment. Our study suggested that AS/WW provides more survival benefits for patients with low-risk PCa. More relevant researches and data will be needed for further clarity.

We attempted to perform risk categories based on the free/total prostate-specific antigen ratio (%fPSA), prostate-specific antigen (PSA) density (PSAD, in ng ml-2), and multiparametric magnetic resonance imaging (mpMRI) step by step, with the goal of determining the best clinical diagnostic strategy to avoid unnecessary tests and prostate biopsy (PBx) in biopsy-naive men with PSA levels ranging from 4 ng ml-1 to 10 ng ml-1. We included 439 patients who had mpMRI and PBx between August 2018 and July 2021 (West China Hospital, Chengdu, China). To detect clinically significant prostate cancer (csPCa) on PBx, receiver-operating characteristic (ROC) curves and their respective area under the curve were calculated. Based on %fPSA, PSAD, and Prostate Imaging-Reporting and Data System (PI-RADS) scores, the negative predictive value (NPV) and positive predictive value (PPV) were calculated sequentially. The optimal %fPSA threshold was determined to be 0.16, and the optimal PSAD threshold was 0.12 for %fPSA ≥0.16 and 0.23 for %fPSA <0.16, respectively. When PSAD <0.12 was combined with patients with %fPSA ≥0.16, the NPV of csPCa increased from 0.832 (95% confidence interval [CI]: 0.766-0.887) to 0.931 (95% CI: 0.833-0.981); the detection rate of csPCa was similar when further stratified by PI-RADS scores (P = 0.552). Combining %fPSA <0.16 with PSAD ≥0.23 ng ml-2 predicted significantly more csPCa patients than those with PSAD <0.23 ng ml-2 (58.4% vs 26.7%, P < 0.001). Using PI-RADS scores 4 and 5, the PPV was 0.739 (95% CI: 0.634-0.827) when further stratified by mpMRI results. In biopsy-naïve patients with PSA level of 4-10 ng ml-1, stratification of %fPSA and PSAD combined with PI-RADS scores may be useful in the decision-making process prior to undergoing PBx. [ABSTRACT FROM AUTHOR]