Urologic oncology
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The COVID-19 public health emergency forced the conversion of in-person SUO fellowship interviews into virtual interviews. We sought to understand applicant perspectives and preferences related to virtual interviews and whether programs should consider virtual interviews in the future. We distributed a survey to 2020 SUO Fellowship interview participants at 4 SUO urologic oncology fellowship programs. ⋯ SUO fellowship applicants exhibited mixed preferences for virtual and in-person interviews. Although virtual fellowship interviews have benefits such as cost savings and time efficiency, notable weaknesses included challenges observing the culture of the programs. Following the pandemic, SUO fellowship programs may consider virtual interviews but should consider incorporating opportunities for informal interactions between faculty, fellows, and fellow applicants.
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To assess potential nosocomial coronavirus disease-2019 (COVID-19) transmission in patients who underwent robot-assisted laparoscopic procedures during the pandemic. ⋯ Robot-assisted laparoscopic surgery seemed safe in the era of COVID-19 as long as all recommended precautions are followed. The rate of nosocomial COVID-19 transmission was extremely low despite the fact that we only used RT-PCR testing in symptomatic patients during the preoperative work-up. Larger cohort is needed to validate these results.
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Radical cystectomy is standard of care and part of a multidisciplinary approach for long-term survival in patients with muscle-invasive bladder cancer (MIBC) or high-grade non-MIBC. Recent data have suggested that anesthetic technique can affect long-term survival and recurrence in patients undergoing cancer related surgery. ⋯ The use of volatile inhalation anesthetics during robot-assisted radical cystectomy may be associated with an increased risk of distant recurrence. Further studies will be necessary to validate these findings.
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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.