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CYP2D6 phenotypes are associated with adverse outcomes related to opioid medications

Overview of attention for article published in Pharmacogenomics and Personalized Medicine, July 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)

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64 Mendeley
Title
CYP2D6 phenotypes are associated with adverse outcomes related to opioid medications
Published in
Pharmacogenomics and Personalized Medicine, July 2017
DOI 10.2147/pgpm.s136341
Pubmed ID
Authors

Jennifer L St Sauver, Janet E Olson, Veronique L Roger, Wayne T Nicholson, John L Black, Paul Y Takahashi, Pedro J Caraballo, Elizabeth J Bell, Debra J Jacobson, Nicholas B Larson, Suzette J Bielinski

Abstract

Variation in the CYP2D6 gene may affect response to opioids in both poor and ultrarapid metabolizers, but data demonstrating such associations have been mixed, and the impact of variants on toxicity-related symptoms (e.g., nausea) is unclear. Therefore, we examined the association between CYP2D6 phenotype and poor pain control or other adverse symptoms related to the use of opioids in a sample of primary care patients. We identified all patients in the Mayo Clinic RIGHT Protocol who were prescribed an opioid medication between July 01, 2013 and June 30, 2015, and categorized patients into three phenotypes: poor, intermediate to extensive, or ultrarapid CYP2D6 metabolizers. We reviewed the electronic health record of these patients for indications of poor pain control or adverse symptoms related to medication use. Associations between phenotype and outcomes were assessed using Chi-square tests and logistic regression. Overall, 257 (25% of RIGHT Protocol participants) patients received at least one opioid prescription; of these, 40 (15%) were poor metabolizers, 146 (57%) were intermediate to extensive metabolizers, and 71 (28%) were ultrarapid metabolizers. We removed patients that were prescribed a CYP2D6 inhibitor medication (n=38). After adjusting for age and sex, patients with a poor or ultrarapid phenotype were 2.7 times more likely to experience either poor pain control or an adverse symptom related to the prescription compared to patients with an intermediate to extensive phenotype (odds ratio: 2.68; 95% CI: 1.39, 5.17; p=0.003). Our results suggest that >30% of patients with a poor or ultrarapid CYP2D6 phenotype may experience an adverse outcome after being prescribed codeine, tramadol, oxycodone, or hydrocodone. These medications are frequently prescribed for pain relief, and ~39% of the US population is expected to carry one of these phenotypes, suggesting that the population-level impact of these gene-drug interactions could be substantial.

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X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 17%
Student > Bachelor 11 17%
Student > Master 11 17%
Other 7 11%
Student > Ph. D. Student 6 9%
Other 7 11%
Unknown 11 17%
Readers by discipline Count As %
Medicine and Dentistry 17 27%
Pharmacology, Toxicology and Pharmaceutical Science 15 23%
Biochemistry, Genetics and Molecular Biology 9 14%
Agricultural and Biological Sciences 2 3%
Nursing and Health Professions 2 3%
Other 6 9%
Unknown 13 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 February 2020.
All research outputs
#5,435,826
of 25,748,735 outputs
Outputs from Pharmacogenomics and Personalized Medicine
#1
of 1 outputs
Outputs of similar age
#85,979
of 327,822 outputs
Outputs of similar age from Pharmacogenomics and Personalized Medicine
#1
of 1 outputs
Altmetric has tracked 25,748,735 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one scored the same or higher as 0 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,822 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them