RESUMEN
PURPOSE: Androgen receptor pathway inhibitors (ARPIs) are widely prescribed in metastatic castration-resistant prostate cancer (mCRPC). Real-world frequencies and potential impacts of comorbidities and concomitant medication (conmed) interactions with ARPIs are not well described. METHODS: Patients receiving ARPIs for mCRPC were identified from the electronic Prostate Cancer Australian Database (ePAD). Demographics, clinicopathologic characteristics, and outcome data were extracted. Conmeds and comorbidities were collected from medical records. Potential interacting comorbidities were defined from trial and post-trial data. Clinically significant drug-drug interactions (DDIs) were identified using UpToDate Lexicomp and Stockley's databases. Patient characteristics, comorbidity interactions, DDIs, and outcomes were analyzed. RESULTS: Two hundred thirty-five patients received first- or second-line ARPIs for mCRPC from 2012 to 2021, with a median follow-up of 27 months. One hundred sixteen received abiraterone acetate (AAP) and 135 received enzalutamide (ENZ). The median age was 74 years, and the median number of conmeds was 4. Clinically significant DDIs occurred in 55 (47%) AAP patients and 90 (67%) ENZ patients. Only 5% of DDIs were predicted to affect ARPI pharmacokinetics (PK) or pharmacodynamics, whereas 95% were predicted to impact conmed PK or increase toxicity risk. In patients receiving ENZ, DDIs were associated with lower PSA50 (50% v 74%, P = .04) and poorer overall survival (28 v 45 months, P = .04), although statistical significance was not maintained on multivariate analysis. No significant survival differences were seen with DDIs in patients receiving AAP. Potential interactions between comorbidities and ARPI were present in 72% on AAP and 14% on ENZ with no significant associated survival differences. CONCLUSION: DDIs and drug-comorbidity interactions in real-world patients receiving ARPIs for mCRPC are common and may affect outcomes. Ongoing clinician education regarding DDIs is necessary to optimize patient outcomes.