Large impacted upper ureter stones: retrograde versus percutaneous anterograde ureteroscopy

The results and complications of two main methods of treatment of 'impacted' stones of the upper third of the ureter: retrograde and percutaneous antegrade ureterolithotripsy - are compared in this article. The main aim of treatment is complete removal of stone to resolve the obstruction, to eliminate the infection, to prevent the growth of stone and to preserve renal function. Computed tomography is included in the standard examination of the patient before the surgery. This article gives an evaluation of effectiveness of percutaneous antegrade ureterolithotripsy as standard method of treatment of 'impacted' stones of the upper third of the ureter.В статье сравниваются результаты и осложнения двух основных методов лечения «вколоченных» камней верхней трети мочеточника: ретроградной и перкутанной антеградной уретеролитотрипсии. Основной целью лечения является полное удаление камня для разрешения обструкции, элиминации инфекции, предотвращения роста камня и сохранения функции почки. В стандарт обследования пациента перед операцией входит компьютерная томография. Статья дает оценку эффективности перкутанной антеградной уретеролитотрипсии, и рассматривает применение перкутанной антеградной уретеролитотрипсии в качестве стандартного метода лечения «вколоченных» камней верхней трети мочеточника

Introducing PIONEER: a project to harness big data in prostate cancer research

Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. Launched by the Innovative Medicines Initiative 2 and part of the Big Data for Better Outcomes Programme (BD4BO), the overarching goal of PIONEER is to provide high-quality evidence on prostate cancer management by unlocking the potential of big data. The project has identified critical evidence gaps in prostate cancer care, via a detailed prioritization exercise including all key stakeholders. By standardizing and integrating existing high-quality and multidisciplinary data sources from patients with prostate cancer across different stages of the disease, the resulting big data will be assembled into a single innovative data platform for research. Based on a unique set of methodologies, PIONEER aims to advance the field of prostate cancer care with a particular focus on improving prostate-cancer-related outcomes, health system efficiency by streamlining patient management, and the quality of health and social care delivered to all men with prostate cancer and their families worldwide.Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe (PIONEER) is a European network of excellence for big data in prostate cancer, consisting of 32 private and public stakeholders from 9 countries across Europe. In this Perspectives article, the authors introduce the PIONEER project and describe its aims and plans for ultimately improving prostate cancer care through the use of big data

How Well do Polygenic Risk Scores Identify Men at High Risk for Prostate Cancer? Systematic Review and Meta-Analysis.

OBJECTIVES: Genome-wide association studies have revealed over 200 genetic susceptibility loci for prostate cancer (PCa). By combining them, polygenic risk scores (PRS) can be generated to predict risk of PCa. We summarize the published evidence and conduct meta-analyses of PRS as a predictor of PCa risk in Caucasian men. PATIENTS AND METHODS: Data were extracted from 59 studies, with 16 studies including 17 separate analyses used in the main meta-analysis with a total of 20,786 cases and 69,106 controls identified through a systematic search of ten databases. Random effects meta-analysis was used to obtain pooled estimates of area under the receiver-operating characteristic curve (AUC). Meta-regression was used to assess the impact of number of single-nucleotide polymorphisms (SNPs) incorporated in PRS on AUC. Heterogeneity is expressed as I(2) scores. Publication bias was evaluated using funnel plots and Egger tests. RESULTS: The ability of PRS to identify men with PCa was modest (pooled AUC 0.63, 95% CI 0.62-0.64) with moderate consistency (I(2) 64%). Combining PRS with clinical variables increased the pooled AUC to 0.74 (0.68-0.81). Meta-regression showed only negligible increase in AUC for adding incremental SNPs. Despite moderate heterogeneity, publication bias was not evident. CONCLUSION: Typically, PRS accuracy is comparable to PSA or family history with a pooled AUC value 0.63 indicating mediocre performance for PRS alone