Metastatic Castration-Resistant Prostate Cancer Previously Treated With Docetaxel-Based Chemotherapy: Treatment Patterns From the PROXIMA Prospective Registry.
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ABSTRACT: PURPOSE:There is a major clinical need to devise an optimal treatment sequence for the multiple therapy options available for patients with metastatic castration-resistant prostate cancer (mCRPC). In the absence of prospective clinical trials, sequencing information can be derived from large, real-world registry studies. PATIENTS AND METHODS:PROXIMA (Treatment Patterns in Patients With Metastatic Castration-Resistant Prostate Cancer Previously Treated With Docetaxel-Based Chemotherapy) is a large, global, prospective registry study evaluating real-world treatment patterns of patients with mCRPC who experience disease progression during or after docetaxel therapy. Patients were enrolled worldwide between 2011 and 2014. Treatments were determined by the treating physicians and recorded in categories of chemotherapy, hormonal therapy, targeted therapy, immunotherapy, and palliative therapy. Treatment sequencing patterns, response to treatment, and types of progression were recorded and analyzed. Progression-free survival and overall survival with different treatment modalities were analyzed using Kaplan-Meier method. RESULTS:Treatment patterns were evaluated in 903 patients. Therapy selection was influenced by region. Hormonal therapy (57.5%) and taxane chemotherapy (26.4%) were the most frequently administered first subsequent treatments after docetaxel. Tumor responses to first subsequent treatment were observed in 22.6% of evaluable patients. Overall survival and progression-free survival did not differ significantly across different treatment modalities. CONCLUSION:Identifying an optimal treatment sequence is vital for improving the care of patients with mCRPC. The PROXIMA registry provided a representative sample of global data on real-world treatment patterns for patients with mCRPC previously treated with docetaxel. These data can be used to devise optimal therapy sequences and inform treatment decisions.
SUBMITTER: Akaza H
PROVIDER: S-EPMC6223517 | biostudies-literature | 2018 Sep
REPOSITORIES: biostudies-literature
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