Urologic oncology
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To develop an international consensus on managing penile cancer patients during the COVID-19 acute waves. A major concern for patients with penile cancer during the coronavirus disease 2019 (COVID-19) pandemic is how the enforced safety measures will affect their disease management. Delays in diagnosis and treatment initiation may have an impact on the extent of the primary lesion as well as the cancer-specific survival because of the development and progression of inguinal lymph node metastases. ⋯ The international consensus panel proposed a framework for the diagnostic and invasive therapeutic procedures for penile cancer within a low-risk environment for COVID-19.
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Comparative Study
Development of robust artificial neural networks for prediction of 5-year survival in bladder cancer.
When exploring survival outcomes for patients with bladder cancer, most studies rely on conventional statistical methods such as proportional hazards models. Given the successful application of machine learning to handle big data in many disciplines outside of medicine, we sought to determine if machine learning could be used to improve our ability to predict survival in bladder cancer patients. We compare the performance of artificial neural networks (ANN), a type of machine learning algorithm, with that of multivariable Cox proportional hazards (CPH) models in the prediction of 5-year disease-specific survival (DSS) and overall survival (OS) in patients with bladder cancer. ⋯ Machine learning algorithms can improve our ability to predict bladder cancer prognosis. Compared to CPH models, ANNs predicted OS more accurately and DSS with similar accuracy. Given the inherent limitations of administrative datasets, machine learning may allow for optimal interpretation of the complex data they contain.