JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
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Predictors of duration of abiraterone acetate in men with castration-resistant prostate cancer.

BACKGROUND: Androgen receptor signaling remains important in castration-resistant prostate cancer (CRPC) as demonstrated by the efficacy of abiraterone acetate (henceforth abiraterone) in phase III trials. Given that heterogeneous patient responses are observed, we sought to identify clinical factors associated with duration of abiraterone.

METHODS: We retrospectively identified patients with CRPC treated with abiraterone in our database. Patient characteristics and types and duration of prostate cancer (PC) therapies were analyzed. These parameters were analyzed with duration of abiraterone in univariate and multivariable analyses.

RESULTS: We identified 161 patients who had received abiraterone. All had received primary androgen-deprivation therapy (ADT), 86% prior secondary hormone therapy (SHT) and 33% prior chemotherapy. The median duration of primary ADT was 23 months, duration of SHT (excluding abiraterone) was 17 months and duration of chemotherapy was 8 months. We demonstrated that lower PSA at abiraterone initiation, longer primary ADT duration, no prior ketoconazole, no prior chemotherapy and longer chemotherapy duration were associated with a longer duration on abiraterone in univariate analysis. In multivariable analysis, duration of primary ADT (duration of abiraterone 9 versus 13 months for ⩽12 versus >12 months, P=0.03) and no use of prior chemotherapy (duration of abiraterone 16 versus 7 months for no versus yes prior chemotherapy, P<0.01) were associated with duration of abiraterone.

CONCLUSIONS: Several clinical parameters, including type and duration of prior therapy, are predictive of responsiveness to abiraterone. These parameters are logical and correlate with smaller disease burden or less exposure to PC therapies. This information can help physicians counsel patients about the potential durability of efficacy of abiraterone. Identifying predictive biomarkers that inform patient selection for therapy is critical to optimizing treatment outcomes.

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