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A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer
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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.

The Urologic Clinics of North America
|November 7, 2017
PubMed
Summary
This summary is machine-generated.

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.

Keywords:
Androgen antagonistCastration resistanceGuidelinesMetastasesProstate cancer

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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.