Refining castration use for recurrent prostate cancer

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Project Summary Project Background: Nearly all US men diagnosed with prostate cancer have localized disease. Most are treated, yet roughly one in three have their prostate cancer return via rising PSA levels. A common treatment for rising PSA is castration with long-acting injectable drugs termed androgen deprivation therapy (ADT). Understanding the best timing of ADT for these men is important because most do not have symptoms of recurrent cancer, yet will deal with major side effects (e.g., diabetes, osteoporosis, obesity, heart disease) in the hopes of survival benefits. However, there is limited evidence to guide castration timing and use when it comes to rising PSA levels after treatment. This results in vague guideline recommendations and widespread practice variation. Whether some men can avoid castration, its side effects, or castration-resistance without compromising survival remains unclear. Using biostatistical models informed by real-world practice variation can refine answers to these important issues. Project Objectives: This study will combine population-based cancer registry and electronic record data from a national delivery system with biostatistical modeling and randomized trial data to examine the impact of castration with ADT on progression and survival after localized prostate cancer treatment. We will take advantage of variable castration practices to identify populations of men that may and may not benefit from castration for recurrent prostate cancer. Project Methods: This clinically-relevant, high impact study has three aims. Aim 1: To examine variation in castration use after localized prostate cancer treatment. We will identify men treated for localized prostate cancer from 2005-2015 using national cancer registry data. We will characterize longitudinal castration practices with respect to timing, continuity, and clinical factors (e.g., PSA, risk group, salvage radiotherapy) using national administrative claims, pharmacy, and laboratory, as well as randomized trial data. Aim 2: To assess the impact of castration timing on prostate cancer progression. We will identify prostate cancer progression to castration-resistant disease among our population-based and randomized trial data. We will use biostatistical modeling to identify castration practices associated with the longest times to castration-resistance and survival outcomes. Aim 3: To refine populations of men most likely to benefit from castration for recurrent prostate cancer, and when. Based on our models and complementary datasets, we will propose criteria and timing for castration practices to help maximize outcomes after localized prostate cancer treatment. For some men, delaying or avoiding castration might be best, for others, earlier castration might be optimal.