Objectives: To present an overall picture of the evidence regarding the association of erectile dysfunction (ED) with cardiovascular disease (CVD). Methods: Systematic reviews and meta‐analyses that studied the association of ED with any CVD were included in this umbrella review. We did not restrict the population to a particular group or age. PubMed, Embase, the Joanna Briggs Institute (JBI) Database of Systematic Reviews and Implementation Reports, the Cochrane Database of Systematic Reviews, the Database of Abstracts of Reviews of Effects, and the PROSPERO register were searched to find relevant systematic reviews, with or without meta‐analyses, from inception to April 2020. The JBI Checklist for Systematic Reviews and Research Syntheses was used for the critical appraisal. Only studies with acceptable quality were included. Two independent reviewers extracted the data using the JBI data extraction tool for qualitative and quantitative data extraction. Results: The summary estimate showed a higher risk of CVD (relative risk [RR] 1.45, 95% confidence interval [CI] 1.36–1.54; P < 0.001), coronary heart disease (RR 1.50, 95% CI 1.37–1.64; P < 0.001), cardiovascular‐related mortality (RR 1.50, 95% CI 1.37–1.64; P < 0.001), all‐cause mortality (RR 1.25, 95% CI 1.18–1.32; P < 0.001), myocardial infarction (RR 1.55, 95% CI 1.33–1.80; P < 0.001) and stroke (RR 1.36, 95% CI 1.26–1.46; P < 0.001) in patients with ED than in other patients. Conclusions: Our results confirm that ED is an independent predictor of CVD and their outcomes. ED and CVD are two presentations of the same physiological phenomenon. ED normally precedes symptomatic CVD, providing a window of opportunity for healthcare practitioners to screen and detect high‐risk patients early to prevent avoidable morbidity and mortality.

Objectives: To perform a systematic review and network meta‐analysis to compare the efficacy and safety of currently available treatments for the management of metastatic hormone‐sensitive prostate cancer (mHSPC), as there has been a paradigm shift with the use of next‐generation androgen receptor inhibitors (ARIs) and docetaxel. Methods: Multiple databases were searched for articles published before May 2020 according to the Preferred Reporting Items for Systematic Review and Meta‐analysis extension statement for network meta‐analysis. Studies comparing overall/progression‐free survival (OS/PFS) and/or adverse events (AEs) in patients with mHSPC were eligible. Results: Nine studies ( N = 9960) were selected, and formal network meta‐analyses were conducted. Abiraterone (hazard ratio [HR] 0.83, 95% credible interval [CrI] 0.76–0.90), docetaxel (HR 0.90, 95% CrI 0.82–0.98), and enzalutamide (HR 0.85, 95% CrI 0.73–0.99) were associated with significantly better OS than androgen‐deprivation therapy (ADT), and abiraterone emerged as the best option. Abiraterone (HR 0.71, 95% CrI 0.67–0.76), apalutamide (HR 0.73, 95% CrI 0.65–0.81), docetaxel (HR 0.84, 95% CrI 0.78–0.90), and enzalutamide (HR 0.67, 95% CrI 0.63–0.71) were associated with significantly better PFS than ADT, and enzalutamide emerged as the best option. Abiraterone (HR 0.85, 95% CrI 0.78–0.93), apalutamide (HR 0.87, 95% CrI 0.77–0.98), and enzalutamide (HR 0.80, 95% CrI 0.73–0.88) were significantly more effective than docetaxel. Regarding AEs, apalutamide was the likely best option among the three ARIs. In patients with low‐volume mHSPC, enzalutamide was the best option in terms of OS and PFS. Conclusions: All three ARIs are effective therapies for mHSPC; apalutamide was the best tolerated. All three seemed more effective than docetaxel. These findings may facilitate individualised treatment strategies and inform future comparative trials.

Objectives: To determine the predictive and prognostic value of a panel of systemic inflammatory response (SIR) biomarkers relative to established clinicopathological variables in order to improve patient selection and facilitate more efficient delivery of peri‐operative systemic therapy. Materials and Methods: The preoperative serum levels of a panel of SIR biomarkers, including albumin–globulin ratio, neutrophil–lymphocyte ratio, De Ritis ratio, monocyte–lymphocyte ratio and modified Glasgow prognostic score were assessed in 4199 patients treated with radical cystectomy for clinically non‐metastatic urothelial carcinoma of the bladder. Patients were randomly divided into a training and a testing cohort. A machine‐learning‐based variable selection approach (least absolute shrinkage and selection operator regression) was used for the fitting of several multivariable predictive and prognostic models. The outcomes of interest included prediction of upstaging to carcinoma invading bladder muscle (MIBC), lymph node involvement, pT3/4 disease, cancer‐specific survival (CSS) and recurrence‐free survival (RFS). The discriminatory ability of each model was either quantified by area under the receiver‐operating curves or by the C‐index. After validation and calibration of each model, a nomogram was created and decision‐curve analysis was used to evaluate the clinical net benefit. Results: For all outcome variables, at least one SIR biomarker was selected by the machine‐learning process to be of high discriminative power during the fitting of the models. In the testing cohort, model performance evaluation for preoperative prediction of lymph node metastasis, ≥pT3 disease and upstaging to MIBC showed a 200‐fold bootstrap‐corrected area under the curve of 67.3%, 73% and 65.8%, respectively. For postoperative prognosis of CSS and RFS, a 200‐fold bootstrap corrected C‐index of 73.3% and 72.2%, respectively, was found. However, even the most predictive combinations of SIR biomarkers only marginally increased the discriminative ability of the respective model in comparison to established clinicopathological variables. Conclusion: While our machine‐learning approach for fitting of the models with the highest discriminative ability incorporated several previously validated SIR biomarkers, these failed to improve the discriminative ability of the models to a clinically meaningful degree. While the prognostic and predictive value of such cheap and readily available biomarkers warrants further evaluation in the age of immunotherapy, additional novel biomarkers are still needed to improve risk stratification.