Second-Line Cabazitaxel Treatment in Castration-Resistant Prostate Cancer Clinical Trials Compared to Standard of Care in CAPRI: Observational Study in the Netherlands.

ABSTRACT

BACKGROUND: Cabazitaxel has been shown to improve overall survival (OS) in metastatic castration-resistant prostate cancer (mCRPC) patients after docetaxel in the TROPIC trial. However, trial populations may not reflect the real-world population. We compared patient characteristics and outcomes of cabazitaxel within and outside trials (standard of care, SOC). PATIENTS AND METHODS: mCRPC patients treated with cabazitaxel directly after docetaxel therapy before 2017 were retrospectively identified and followed to 2018. Patients were grouped on the basis of treatment within a trial or SOC. Outcomes included OS and prostate-specific antigen (PSA) response. RESULTS: From 3616 patients in the CAPRI registry, we identified 356 patients treated with cabazitaxel, with 173 patients treated in the second line. Trial patients had favorable prognostic factors fewer symptoms, less visceral disease, lower lactate dehydrogenase, higher hemoglobin, more docetaxel cycles, and longer treatment-free interval since docetaxel therapy. PSA response (≥ 50% decline) was 28 versus 12%, respectively (P = .209). Median OS was 13.6 versus 9.6 months for trial and SOC subgroups, respectively (hazard ratio = 0.73, P = .067). After correction for prognostic factors, there was no difference in survival (hazard ratio = 1.00, P = .999). Longer duration of androgen deprivation therapy treatment, lower lactate dehydrogenase, and lower PSA were associated with longer OS; visceral disease had a trend for shorter OS. CONCLUSION: Patients treated with cabazitaxel in trials were fitter and showed outcomes comparable to registration trials. Conversely, those treated in daily practice showed features of more aggressive disease and worse outcome. This underlines the importance of adequate estimation of trial eligibility and health status of mCRPC patients in daily practice to ensure optimal outcomes.