Background: Prostate cancer (PCa) is the most common non-skin cancer affecting American men. Two common NHTs used to treat PCa are enzalutamide and abiraterone. Due to the different mechanisms of these two NHTs, we hypothesized that the concomitant medications prescribed might be related to therapy-related adverse effects. The purpose of this study was to examine whether changes in concomitant medications depended on the NHT prescribed. Methods: Medicare patients with a prescription of either enzalutamide or abiraterone in the Surveillance, Epidemiology, and End Results (SEER)–Medicare database diagnosed with prostate cancer from January 01, 2004 to December 31, 2015 were included. Medications were classified by Lexicomp’s pharmacologic category. Only oral prescriptions were included. McNemar’s test was used to compare the drug use prevalence of each category prior to and after initiation of NHT. Generalized logistic regression was used to evaluate whether changes in prescription drug class during the 6 months post-NHT initiation periods depended on the type of NHT. Results: Among the 1067 patients included, 354 were prescribed enzalutamide and 713 were prescribed abiraterone. We found statistically significant interactions between NHT (enzalutamide vs. abiraterone) and period (post vs. preinitiation NHT). Patients prescribed enzalutamide were more likely to discontinue prescriptions for steroids (p<0.01) as expected. The odds of fluoroquinolones, non-steroidal anti-inflammatory drugs (NSAIDs), and loop diuretics prescriptions were similar pre-NHT initiation for both enzalutamide and abiraterone patients; however, patients treated with enzalutamide were significantly less likely than abiraterone patients to have post-NHT initiation prescriptions for fluoroquinolones (Odds ratio (OR) 0.69 p=0.01) or loop diuretics (OR: 0.57 p<0.01). Conclusions: To our knowledge, this is the first population-based study to describe concurrent medication prescribing before and after NHT. Further studies are warranted to better understand the underlying reasons for the observed patterns.