Journal
PHARMACOGENOMICS & PERSONALIZED MEDICINE
Volume 14, Issue -, Pages 229-237Publisher
DOVE MEDICAL PRESS LTD
DOI: 10.2147/PGPM.S281645
Keywords
pharmacogenomics; emergency department; hospitalization
Categories
Funding
- CTSA from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH) [UL1 TR002377]
- Mayo Clinic Center for Individualized Medicine
Ask authors/readers for more resources
This study found no association between 10 well-established pharmacogenomics phenotypes and hospitalization or ED visits. Traditional risk factors like age and self-rated health were more predictive of hospitalization and/or ED visits than pharmacogenomics information.
Background: The use of pharmacogenomics data is increasing in clinical practice. However, it is unknown if pharmacogenomics data can be used more broadly to predict outcomes like hospitalization or emergency department (ED) visit. We aim to determine the association between selected pharmacogenomics phenotypes and hospital utilization outcomes (hospitalization and ED visits). Methods: This cohort study utilized 10,078 patients from the Mayo Clinic Biobank in the RIGHT protocol with sequence and interpreted phenotypes for 10 selected pharmacogenes including CYP2D6, CYP2C9, CYP2C19, CYP3A5, HLA B 5701, HLA B 5702, HLA B 5801, TPMT, SLCO1B1, and DPYD. The primary outcome was hospitalization with ED visits as a secondary outcome. We used Cox proportional hazards model to test the association between each pharmacogenomics phenotype and the risk of the outcomes. Results: During the follow-up period (median [in years] = 7.3), 13% (n=1354) and 8% (n=813) of the subjects experienced hospitalization and ED visits, respectively. Compared to subjects who did not experience hospitalization, hospitalized patients were older (median age [in years]: 67 vs 65), poorer self-rated health (15% vs 4.7% for fair/poor), and higher disease burden (median number of chronic conditions: 7 vs 4) at baseline. There was no association of hospitalization with any of the pharmacogenomics phenotypes. The pharmacogenomics phenotypes were not associated with disease burden, a well-established risk factor for hospital utilization outcomes. Similar findings were observed for patients with ED visits during the follow-up period. Conclusion: We found no association of 10 well-established pharmacogenomics phenotypes with either hospitalization or ED visits in this relatively large biobank population and outside the context of specific drug use related to these genes. Traditional risk factors for hospitalization like age and self-rated health were much more likely to predict hospitalization and/or ED visits than this pharmacogenomics information.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available