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A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer
Published on: March 6, 2018
Castration-Resistant Prostate Cancer: An Algorithmic Approach
Kelly Stratton1, Michael Cookson1
1Department of Urology, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 920 Stanton L. Young BLVD, WP 3150, Oklahoma City, OK 73104, USA.
Abstract:
Since 2010, 5 new agents have been approved for advanced prostate cancer treatment. The American Urologic Association (AUA) published guidelines for the management of castration-resistant prostate cancer in 2013. These guidelines identify 6 index patients to consider when selecting the most appropriate treatment. No comparative trials have provided an approach to optimize the sequencing of these drugs. For the urologist, incorporating the guidelines into clinical practice typically requires a multidisciplinary team. This article provides an algorithmic approach based on indication and mechanism of action that complements the AUA guidelines to ensure patients receive the most optimal care.
Insights
Advanced prostate cancer treatment has seen 5 new agents approved since 2010. This article offers an algorithm to optimize drug sequencing, complementing existing guidelines for better patient care.
Area of Science:
- Oncology
- Urology
Background:
- Five new agents for advanced prostate cancer approved since 2010.
- American Urologic Association (AUA) guidelines for castration-resistant prostate cancer management published in 2013.
- AUA guidelines identify 6 index patients for treatment selection.
Purpose of the Study:
- To provide an algorithmic approach for optimizing the sequencing of advanced prostate cancer treatments.
- To complement the existing AUA guidelines with a practical clinical tool.
- To aid urologists in selecting the most appropriate treatment based on indication and mechanism of action.
Main Methods:
- Development of an algorithmic approach for prostate cancer treatment sequencing.
- Integration of drug indication and mechanism of action into the algorithm.
- Complementary strategy to existing AUA clinical guidelines.
Main Results:
- An algorithmic approach is presented to guide treatment sequencing.
- The algorithm aims to optimize care by considering drug properties.
- This approach supports clinical decision-making for urologists.
Conclusions:
- An algorithmic approach can enhance the application of AUA guidelines for advanced prostate cancer.
- Optimizing drug sequencing is crucial for effective patient management.
- Multidisciplinary collaboration is essential for integrating these strategies into practice.
