Abstract
Background
Cytochrome P450 2D6 (CYP2D6) is responsible for the metabolism of clinically used drugs and other environmental exposures, but it is unclear whether the CYP2D6 phenotype is associated with adverse health outcomes. The aim was to determine the association of CYP2D6 phenotype with the risk of hospitalization or an emergency department (ED) visit among a group of primary care patients.
Methods
In this study, 929 adult patients underwent CYP2D6 testing. The primary outcome was risk of hospitalization or an ED visit from January 2005 through September 2014. CYP2D6 genotypes were interpreted as 1 of 7 clinical phenotypes, from ultrarapid to poor metabolizer, and patients with the extensive metabolizer phenotype were used as the reference group. The hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated for finding the association of CYP2D6 phenotypes with the risk of hospitalization or an ED visit by using Cox proportional hazard models and adjusting for age and sex.
Results
The median age was 49 years (interquartile range, 46–52 years); 74% of patients had 3 or fewer chronic conditions, 285 had at least 1 hospitalization, and 496 had at least 1 ED visit. The risk of hospitalization was higher among patients who were ultrarapid metabolizers compared to extensive metabolizers (47% vs 30%; HR, 1.69; 95% CI, 1.11–2.57), as was the risk of an ED visit (62% vs 49%; HR, 1.50; 95% CI, 1.05–2.14). For poor metabolizers compared to extensive metabolizers, there was no difference in the risk of hospitalization (HR, 0.95; 95% CI, 0.58–1.56), but there was an increase in the risk of an ED visit (HR, 1.38; 95% CI, 0.96–1.98) (the difference was not statistically significant).
Conclusion
We found an increased risk of hospitalization or an ED visit among ultrarapid compared to extensive CYP2D6 metabolizers. Further research identifying the mechanisms of the association and ultimate clinical utility is warranted.
Acknowledgments
We acknowledge Kari Takahashi, MEd, for copyediting the manuscript.
This work was supported in part by Mayo Clinic Center for Individualized Medicine, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, National Institutes of Health grants U19 GM61388 (The Pharmacogenomics Research Network), R01 GM28157, U01 HG005137, R01 CA138461, R01 AG034676 (The Rochester Epidemiology Project), and U01 HG06379 and U01 HG06379 Supplement (The Electronic Medical Record and Genomics [eMERGE] Network).
Disclosure
PYT serves on the medical advisory board for Axial, LLC. JLB and Mayo Clinic have licensed pharmacogenomic drug selection algorithms to Assurex Health and OneOme. The other authors report no conflicts of interest in this work.