Modeling the Relationship Between Exposure to Abiraterone and Prostate-Specific Antigen Dynamics in Patients with Metastatic Castration-Resistant Prostate Cancer

• Published in: Clinical pharmacokinetics 2017, Vol.56 (1), p.55-63
• Main Authors: Xu, Xu Steven, Ryan, Charles J., Stuyckens, Kim, Smith, Matthew R., Saad, Fred, Griffin, Thomas W., Park, Youn C., Yu, Margaret K., De Porre, Peter, Vermeulen, An, Poggesi, Italo, Nandy, Partha
• Format: Article
• Language: English
• Subjects: Abiraterone Acetate - administration & dosage; Abiraterone Acetate - pharmacokinetics; Androgens; Antigens; Area Under Curve; Breast cancer; Chemotherapy; Clinical trials; Drug dosages; Drug Therapy, Combination; Humans; Internal Medicine; L-Lactate Dehydrogenase - blood; Laboratories; Male; Medicine; Medicine & Public Health; Metastasis; Models, Biological; Original Research Article; Patients; Pharmacology/Toxicology; Pharmacotherapy; Prednisone - administration & dosage; Prednisone - pharmacokinetics; Prednisone - pharmacology; Prostate cancer; Prostate-Specific Antigen - drug effects; Prostatic Neoplasms, Castration-Resistant - drug therapy; Severity of Illness Index; Socioeconomic Factors; Studies; Survival analysis; Testosterone - blood
• ISSN: 0312-5963; 1179-1926
• DOI: 10.1007/s40262-016-0425-0

Background and Objectives Recent analysis revealed strong associations between prostate-specific antigen (PSA) dynamics and overall survival (OS) in metastatic castration-resistant prostate cancer (mCRPC) and supported PSA dynamics as bridging surrogacy endpoints for clinical benefit from treatment with abiraterone acetate plus prednisone. This analysis aimed to investigate the abiraterone exposure–PSA dynamics relationship in mCRPC. Methods Abiraterone pharmacokinetics–PSA models were constructed using data from the COU-AA-301 (chemotherapy-pretreated) and COU-AA-302 (chemotherapy-naïve) trials comparing abiraterone acetate 1000 mg/day plus prednisone 5 mg twice daily with prednisone alone in mCRPC. The drug effect–PSA dynamics relationship was modeled as a function of selected pharmacokinetic measures. The influences of baseline demographic variables, laboratory values, and disease status on PSA dynamics were assessed. Results A tumor growth inhibition model best described PSA dynamics post-treatment with abiraterone acetate. Abiraterone acetate treatment in chemotherapy-pretreated and chemotherapy-naïve patients increased the PSA decay rate ( k dec ) to the same extent (1.28-fold, 95 % confidence interval [CI] 0.58–1.98; and 0.93-fold, 95 % CI 0.6–1.27, respectively). Lower baseline lactate dehydrogenase and higher baseline testosterone significantly increased k dec . Findings from our analysis suggest a maximum-effect relationship between abiraterone trough concentration and PSA dynamics in both patient populations. The majority of patients had a steady-state trough concentration greater than the estimated half maximal effective concentration. Conclusion The model appropriately described the exposure–response relationship between abiraterone and PSA dynamics in chemotherapy-pretreated and chemotherapy-naïve patients following oral administration of abiraterone acetate.