Ep. 103 Adjuvant Treatment for High Risk Bladder Cancer with Dr. Yair Lotan and Suzanne Cole

BackTable Urology - A podcast by BackTable - Tuesdays

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In this episode of BackTable Urology, Dr. Aditya Bagrodia invites Dr. Yair Lotan, professor of urologic oncology at UT Southwestern, and oncologist Dr. Suzanne Cole to discuss types of adjuvant treatment for high risk bladder cancer, including chemotherapy, radiation therapy, and immunotherapy. --- CHECK OUT OUR SPONSOR Veracyte https://www.veracyte.com/decipher --- SHOW NOTES First, they discuss the benefits of neoadjuvant chemotherapy for bladder cancer, which includes a 5-10% absolute advantage and a 20% reduction in likelihood of dying. They also discuss potential barriers to neoadjuvant chemotherapy and the importance of having a discussion with a medical oncologist to determine eligibility for cisplatin-based treatment, such as MVAC chemotherapy. Next, they explore the differences between adjuvant and salvage therapy, as well as how to approach post-operative complications and counseling; it is important to discuss the risk of disease recurrence and initiate conversations about future chemotherapy early in treatment. Then, the doctors explore when to consider immunotherapy instead of cisplatin-based chemotherapy, the success rates of chemotherapy treatments, and the potential of cell-free DNA testing to predict outcomes. They consider the implications of false negatives and false positives and agree that clinical trials are important to gain a better understanding of the technology and how it could be used in personalized medicine. They also discuss when radiation therapy is appropriate for recurrence in the retroperitoneum and the use of metallic clips to create a target zone for radiation oncologists. Finally, they consider the difficulty of convincing patients to accept additional therapy and the lack of level 1 evidence for adjuvant therapy. However, they remain optimistic about the progress being made with upper tract studies, innovative new treatments, and the potential of biomarkers to predict response.

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