Exposure-response analyses of abiraterone and its metabolites in real-world patients with metastatic castration-resistant prostate cancer

Autor: van Nuland, M, Groenland, S L, Bergman, A M, Steeghs, N, Rosing, H, Venekamp, N, Huitema, A D R, Beijnen, J H
Přispěvatelé: Afd Pharmacoepi & Clinical Pharmacology, Pharmacoepidemiology and Clinical Pharmacology
Jazyk: angličtina
Rok vydání: 2020
Popis: BACKGROUND: Abiraterone acetate is an oral 17α-hydroxylase/C17,20-lyase (CYP17) inhibitor approved for the treatment of metastatic castration-resistant prostate cancer (mCPRC) patients. Previously, a prospective observational trial demonstrated a relationship between abiraterone trough concentrations (Cmin) in plasma and treatment efficacy. The aim of our study was to investigate the exposure-response relationship of abiraterone and its metabolites, and to study if the proposed target for abiraterone of 8.4 ng/mL is feasible in a "real-world" patient cohort. PATIENTS AND METHODS: mCRPC patients who had at least one abiraterone plasma concentration at steady-state were included in this study. Plasma abiraterone and its metabolites levels were analyzed using a validated liquid chromatography-mass spectrometry method. Using calculated Cmin values of abiraterone and its active metabolite Δ(4)-abiraterone (D4A), univariate, and multivariable Cox regression analyses were performed. RESULTS: Sixty-two patients were included in this retrospective analysis, of which 42% were underexposed (mean abiraterone Cmin ≤ 8.4 ng/mL). In multivariable analysis, Cmin ≥ 8.4 ng/mL was associated with longer prostate-specific antigen (PSA) independent progression-free survival (16.9 vs 6.1 months; p = 0.033), which resulted in a hazard ratio of 0.44 (95% confidence interval: 0.23-0.82, p = 0.01). D4A Cmin did not show a relationship with treatment efficacy. CONCLUSION: Our study shows that mCRPC patients with an abiraterone Cmin ≥ 8.4 ng/mL have a better prognosis compared with patients with low Cmin. Monitoring Cmin of abiraterone can help to identify those patients at risk of suboptimal treatment for whom treatment optimization may be appropriate.
Databáze: OpenAIRE