Pseudoneoplastic lesions of the testis and paratesticular structures

Pseudotumors or tumor-like proliferations (non-neoplastic masses) and benign mimickers (non-neoplastic cellular proliferations) are rare in the testis and paratesticular structures. Clinically, these lesions (cysts, ectopic tissues, and vascular, inflammatory, or hyperplastic lesions) are of great interest for the reason that, because of the topography, they may be relevant as differential diagnoses. The purpose of this paper is to present an overview of the pseudoneoplasic entities arising in the testis and paratesticular structures; emphasis is placed on how the practicing pathologist may distinguish benign mimickers and pseudotumors from true neoplasia. These lesions can be classified as macroscopic or microscopic mimickers of neoplasia

Short-term forecasts to inform the response to the Covid-19 epidemic in the UK

AbstractBackgroundShort-term forecasts of infectious disease can aid situational awareness and planning for outbreak response. Here, we report on multi-model forecasts of Covid-19 in the UK that were generated at regular intervals starting at the end of March 2020, in order to monitor expected healthcare utilisation and population impacts in real time.MethodsWe evaluated the performance of individual model forecasts generated between 24 March and 14 July 2020, using a variety of metrics including the weighted interval score as well as metrics that assess the calibration, sharpness, bias and absolute error of forecasts separately. We further combined the predictions from individual models into ensemble forecasts using a simple mean as well as a quantile regression average that aimed to maximise performance. We compared model performance to a null model of no change.ResultsIn most cases, individual models performed better than the null model, and ensembles models were well calibrated and performed comparatively to the best individual models. The quantile regression average did not noticeably outperform the mean ensemble.ConclusionsEnsembles of multi-model forecasts can inform the policy response to the Covid-19 pandemic by assessing future resource needs and expected population impact of morbidity and mortality.</jats:sec