Number of Prescription Medications and Overall Survival in Metastatic Castrate-Resistant Prostate Cancer

转移性去势抵抗性前列腺癌患者的处方药物数量与总生存期

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Abstract

Background: Assessment of comorbid diseases is essential to clinical research and may risk-stratify patients for mortality independent of established methods such as the Charlson Comorbidity Index (CCI). Methods: In a retrospective study of U.S. Veterans, we examined the association between the number of medications, 1-year mortality, and overall survival in Veterans being treated for metastatic castration-resistant prostate cancer (mCRPC) between 2011 and 2017. Results: Among 8855 Veterans, a median of 11 medications and 6 medication classes were filled in the year prior to initial treatment of mCRPC with abiraterone or enzalutamide. The median patient age was 74 years, 25.7% of patients were Black, and the median CCI was 3. Despite being associated with fewer medications, increasing age was associated with an increased CCI. After adjusting for patient, tumor, and treatment factors, both the number of medications and the number of medication classes were associated with increased 1-year mortality with adjusted OR (95% CI) of 1.03 (1.03, 1.04) and 1.08 (1.06, 1.11), respectively. Medications within Anatomic Therapeutic Class (ATC) N (nervous system) and ATC G (genitourinary and sex hormones) were associated with decreased OS, HR 1.18 (1.11, 1.25) and HR 1.15 (1.10, 1.20), respectively. Medications within ATC C (cardiovascular) were associated with increased OS, HR 0.91 (0.86, 0.97). Within a subgroup of patients with comparable age and CCI, the increased number of medications was associated with the increased risk of death. Conclusions: The number and type of medications were independently associated with survival in patients undergoing treatment for mCRPC. With new therapies for treatment of advanced prostate cancer, patients are living longer, which increases the need for better understanding of the impact of comorbid diseases. Simple methods to assess disease burden and prognosticate survival have the potential to guide treatment decisions and improve the quality of life in this patient population.

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