Bmc Med
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Choosing or altering the planned statistical analysis approach after examination of trial data (often referred to as 'p-hacking') can bias the results of randomised trials. However, the extent of this issue in practice is currently unclear. We conducted a review of published randomised trials to evaluate how often a pre-specified analysis approach is publicly available, and how often the planned analysis is changed. ⋯ Unexplained discrepancies in the statistical methods of randomised trials are common. Increased transparency is required for proper evaluation of results.
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Understanding of the role of ethnicity and socioeconomic position in the risk of developing SARS-CoV-2 infection is limited. We investigated this in the UK Biobank study. ⋯ Some minority ethnic groups have a higher risk of confirmed SARS-CoV-2 infection in the UK Biobank study, which was not accounted for by differences in socioeconomic conditions, baseline self-reported health or behavioural risk factors. An urgent response to addressing these elevated risks is required.
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The five-tiered Cambridge Prognostic Group (CPG) classification is a better predictor of prostate cancer-specific mortality than the traditional three-tiered classification (low, intermediate, and high risk). We investigated radical treatment rates according to CPG in men diagnosed with non-metastatic prostate cancer in England between 2014 and 2017. ⋯ The CPG classification distributes men in five risk groups that are about equal in size. It reveals differences in treatment practices in men with intermediate-risk disease (CPG2 and CPG3) and in men with high-risk disease (CPG4 and CPGP5) that are not visible when using the traditional three-tiered risk classification.
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We are currently experiencing an unprecedented challenge, managing and containing an outbreak of a new coronavirus disease known as COVID-19. While China-where the outbreak started-seems to have been able to contain the growth of the epidemic, different outbreaks are nowadays present in multiple countries. Nonetheless, authorities have taken action and implemented containment measures, even if not everything is known. ⋯ Many quantitative aspects of the natural history of the disease are still unknown, such as the amount of possible asymptomatic spreading or the role of age in both the susceptibility and mortality of the disease. However, preparedness plans and mitigation interventions should be ready for quick and efficacious deployment globally. The scenarios evaluated here through data-driven simulations indicate that measures aimed at reducing individuals' flow are much less effective than others intended for early case identification and isolation. Therefore, resources should be directed towards detecting as many and as fast as possible the new cases and isolate them.