Prostate Cancer: Management of Biochemical Recurrence after Surgery

Radical prostatectomy (RP) is one of the primary treatment options for localised prostate cancer (PCa). Despite its curativeintent, 1/3 of patients will experience biochemical recurrence (BCR) during follow-up. Experts have devoted efforts to associatethe influence of each individual factor with the risk of BCR to select the optimal treatment for each patient. Optimal managementmust aim to find a balance between delaying the onset of metastatic disease and overtreating an indolent disease with treatmentsthat can affect quality of life of the patients. Thus far, effective treatment options for men with BCR remain controversial interms of ideal treatment timing (adjuvant vs. salvage), radiotherapy (RT) fields and doses, selection and duration of systemictherapy and potential synergies between treatments and their therapeutic sequencing. Next-generation imaging techniques, suchas Prostate-Specific Membrane Antigen Positron Emission Tomography, are used for early detection of disease progression andexact site of recurrence or progression, thereby enhancing decision making for future disease management. In this review, weevaluate available evidence of controversial topics regarding BCR after RP and explore future directions, such as prognosticand/or predictive factors of response, genetic panels, second-generation hormone treatments, ultra-hypofractionated RT andongoing clinical trials in this clinical scenario. (AU)

Prostate Cancer: Management of Biochemical Recurrence after Surgery.

Radical prostatectomy (RP) is one of the primary treatment options for localised prostate cancer (PCa). Despite its curative intent, 1/3 of patients will experience biochemical recurrence (BCR) during follow-up. Experts have devoted efforts to associate the influence of each individual factor with the risk of BCR to select the optimal treatment for each patient. Optimal management must aim to find a balance between delaying the onset of metastatic disease and overtreating an indolent disease with treatments that can affect quality of life of the patients. Thus far, effective treatment options for men with BCR remain controversial in terms of ideal treatment timing (adjuvant vs. salvage), radiotherapy (RT) fields and doses, selection and duration of systemic therapy and potential synergies between treatments and their therapeutic sequencing. Next-generation imaging techniques, such as Prostate-Specific Membrane Antigen Positron Emission Tomography, are used for early detection of disease progression and exact site of recurrence or progression, thereby enhancing decision making for future disease management. In this review, we evaluate available evidence of controversial topics regarding BCR after RP and explore future directions, such as prognostic and/or predictive factors of response, genetic panels, second-generation hormone treatments, ultra-hypofractionated RT and ongoing clinical trials in this clinical scenario.

COVID-19 pneumonia treated with ultra-low doses of radiotherapy (ULTRA-COVID study): a single institution report of two cases.

INTRODUCTION: Since the outbreak of coronavirus disease 2019 (COVID-19) pandemic, healthcare systems have focused their efforts into finding a treatment to avoid the fatal outcomes of severe acute respiratory syndrome due to coronavirus­2 (SARS-CoV-2). Benefits and risks of systemic treatments remain unclear, with multiple clinical trials still ongoing. Radiotherapy could play a role in reducing the inflammatory response in the lungs and relieve life-threatening symptoms. METHODS: We designed a prospective study of Ultra-Low Doses of Therapy with Radiation Applied to COVID-19 (ULTRA-COVID) for patients who suffer pneumonia, are not candidates for invasive mechanical ventilation and show no improvement with medical therapy. RESULTS: We present the preliminary results of two patients diagnosed with COVID-19 pneumonia treated with ULTRA-COVID. After one radiotherapy session, significant clinical response and a good radiological response was observed in both cases, resulting in both patients being discharged from hospital in less than 2 weeks after radiation treatment. CONCLUSION: Preliminary clinical and radiological results suggest a potential benefit of treating COVID-19 pneumonia with ULTRA-COVID. ClinicalTrials.gov Identifier: NCT04394182.

Spanish risk management framework across 17 radiation oncology centers during COVID-19 pandemic.

The COVID-19 pandemic has impacted our healthcare systems and the rapid introduction of new protocols that have been required to keep patients and workforce safe. In order to maintain activity with radiotherapy clinical assistance, we have implemented different measures in our centers from a patient and staff safety perspective.

Estudio preliminar sobre extracción automática del tamaño tumoral para la estadificación del cáncer de mama a partir de texto libre de informes clínicos / Preliminary study of automatic extraction of breast cancer staging from free text clinical reports

Objetivo. El estadio del cáncer de mama constituye uno de los factores pronósticos más relevantes. Sin embargo, la compleja clasificación TNM, la existencia de diferentes versiones y la variabilidad de la fuente de la información hacen que la recogida de datos sobre texto libre sea compleja. El objetivo de este trabajo es desarrollar una herramienta que permita ayudar a la estadificación de manera automática. Pacientes y métodos. El trabajo incluyó el estudio de los informes de 100 pacientes con cáncer de mama no metastásico tratadas con cirugía y radioterapia en 2012. La recogida del tamaño tumoral posquirúrgico (séptima edición TNM) se realizó con la herramienta desarrollada y manualmente por un médico en formación especializada de tercer año de oncología radioterápica. Resultados. La aplicación fue capaz de detectar el 62% de los casos tras examinar los informes de anatomía patológica, y el 77% al añadir el examen de los informes de oncología radioterápica. Los casos no detectados se debieron a que la información estaba almacenada en otra sección de la estación clínica. Comparando los resultados entre la aplicación y la recogida manual, hubo una diferencia del 13% (10/77). Se observó que en el 50% de los casos (5/10) la aplicación era correcta, mientras que en el otro 50% lo fue la recogida manual. Conclusiones. Esta herramienta innovadora permite recoger automáticamente el tamaño tumoral en el cáncer de mama, ahorrando tiempo en la recogida de datos y evitando errores en la clasificación tumoral, por lo que puede contribuir de modo notable en la decisión terapéutica(AU)

Objective. Staging of breast cancer is one of the most important prognostic factors. However, collecting data for staging manually from unstructured free text is variable and imprecise because of the complexity of the TNM classification, the existence of different versions over time, and variability in the source used to obtain data. The aim of this study was to develop an artificial intelligence tool to allow data on tumoral staging to be mined automatically. Patients and methods. The study included the reports of the first 100 patients with nonmetastatic breast cancer treated with surgery and radiotherapy in 2012. Data on postoperative tumor size (TNM seventh edition) were collected with a specially designed software tool and manually by a third-year resident physician in radiation oncology. Results. The software application detected 62% of cases when pathology reports were included, and 77% when radiation oncology reports were added. Non-detection was due to the information being stored in another section of the clinical station. When we compared the results of the software application and manual collection, we found a difference of 13% (10/77). In these 10 cases, the application was correct in 50%, while manual collection was correct in the remaining 50%. Conclusions. This innovative system allows automatic staging of tumoral size in breast cancer. The use of this tool would save time in data collection and prevent errors in tumoral classification and could also improve therapeutic decisions(AU)