Dataset Information

Drug-gene and drug-drug interactions associated with tramadol and codeine therapy in the INGENIOUS trial.

ABSTRACT: Background: Tramadol and codeine are metabolized by CYP2D6 and are subject to drug-gene and drug-drug interactions. Methods: This interim analysis examined prescribing behavior and efficacy in 102 individuals prescribed tramadol or codeine while receiving pharmaco-genotyping as part of the INGENIOUS trial (NCT02297126). Results: Within 60 days of receiving tramadol or codeine, clinicians more frequently prescribed an alternative opioid in ultrarapid and poor metabolizers (odds ratio: 19.0; 95% CI: 2.8-160.4) as compared with normal or indeterminate metabolizers (p = 0.01). After adjusting the CYP2D6 activity score for drug-drug interactions, uncontrolled pain was reported more frequently in individuals with reduced CYP2D6 activity (odds ratio: 0.50; 95% CI: 0.25-0.94). Conclusion: Phenoconversion for drug-drug and drug-gene interactions is an important consideration in pharmacogenomic implementation; drug-drug interactions may obscure the potential benefits of genotyping.

SUBMITTER: Fulton CR

PROVIDER: S-EPMC6562829 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Drug-gene and drug-drug interactions associated with tramadol and codeine therapy in the INGENIOUS trial.

Fulton Cathy R CR Zang Yong Y Desta Zeruesenay Z Rosenman Marc B MB Holmes Ann M AM Decker Brian S BS Zhang Yifei Y T Callaghan John J Pratt Victoria M VM Levy Kenneth D KD Gufford Brandon T BT Dexter Paul R PR Skaar Todd C TC Eadon Michael T MT

Pharmacogenomics 20190220 6

Background: Tramadol and codeine are metabolized by CYP2D6 and are subject to drug-gene and drug-drug interactions. Methods: This interim analysis examined prescribing behavior and efficacy in 102 individuals prescribed tramadol or codeine while receiving pharmaco-genotyping as part of the INGENIOUS trial (NCT02297126). Results: Within 60 days of receiving tramadol or codeine, clinicians more frequently prescribed an alternative opioid in ultrarapid and poor metabolizers (od ...[more]

PMID: 30784356

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Project description:ImportanceAlthough tramadol is increasingly used to manage chronic noncancer pain, few safety studies have compared it with other opioids.ObjectiveTo assess the associations of tramadol, compared with codeine, with mortality and other adverse clinical outcomes as used in outpatient settings.Design, setting, and participantsRetrospective, population-based, propensity score-matched cohort study using a primary care database with routinely collected medical records and pharmacy dispensations covering more than 80% of the population of Catalonia, Spain (≈6 million people). Patients 18 years or older with 1 or more year of available data and dispensation of tramadol or codeine (2007-2017) were included and followed up to December 31, 2017.ExposuresNew prescription dispensation of tramadol or codeine (no dispensation in the previous year).Main outcomes and measuresOutcomes studied were all-cause mortality, cardiovascular events, fractures, constipation, delirium, falls, opioid abuse/dependence, and sleep disorders within 1 year after the first dispensation. Absolute rate differences (ARDs) and hazard ratios (HRs) with 95% confidence intervals were calculated using cause-specific Cox models.ResultsOf the 1 093 064 patients with a tramadol or codeine dispensation during the study period (326 921 for tramadol, 762 492 for codeine, 3651 for both drugs concomitantly), a total of 368 960 patients (184 480 propensity score-matched pairs) were included after study exclusions and propensity score matching (mean age, 53.1 [SD, 16.1] years; 57.3% women). Compared with codeine, tramadol dispensation was significantly associated with a higher risk of all-cause mortality (incidence, 13.00 vs 5.61 per 1000 person-years; HR, 2.31 [95% CI, 2.08-2.56]; ARD, 7.37 [95% CI, 6.09-8.78] per 1000 person-years), cardiovascular events (incidence, 10.03 vs 8.67 per 1000 person-years; HR, 1.15 [95% CI, 1.05-1.27]; ARD, 1.36 [95% CI, 0.45-2.36] per 1000 person-years), and fractures (incidence, 12.26 vs 8.13 per 1000 person-years; HR, 1.50 [95% CI, 1.37-1.65]; ARD, 4.10 [95% CI, 3.02-5.29] per 1000 person-years). No significant difference was observed for the risk of falls, delirium, constipation, opioid abuse/dependence, or sleep disorders.Conclusions and relevanceIn this population-based cohort study, a new prescription dispensation of tramadol, compared with codeine, was significantly associated with a higher risk of subsequent all-cause mortality, cardiovascular events, and fractures, but there was no significant difference in the risk of constipation, delirium, falls, opioid abuse/dependence, or sleep disorders. The findings should be interpreted cautiously, given the potential for residual confounding.

Project description:Recruitment of diverse populations and subjects living in Medically Underserved Areas and Populations (MUA/P's) into clinical trials is a considerable challenge. Likewise, representation of African-Americans in pharmacogenetic trials is often inadequate, but critical for identifying genetic variation within and between populations. To identify enrollment patterns and variables that predict enrollment in a diverse underserved population, we analyzed data from the INGENIOUS (Indiana GENomics Implementation and Opportunity for the UnderServed), pharmacogenomics implementation clinical trial conducted at a community hospital for underserved subjects (Safety net hospital), and a statewide healthcare system (Academic hospital). We used a logistic regression model to identify patient variables that predicted successful enrollment after subjects were contacted and evaluated the reasons that clinical trial eligible subjects refused enrollment. In both healthcare systems, African-Americans were less likely to refuse the study than non-Hispanic Whites (Safety net, OR = 0.68, and p < 0.002; Academic hospital, OR = 0.64, and p < 0.001). At the Safety net hospital, other minorities were more likely to refuse the study than non-Hispanic Whites (OR = 1.58, p < 0.04). The odds of refusing the study once contacted increased with patient age (Safety net hospital, OR = 1.02, p < 0.001, Academic hospital, OR = 1.02, and p < 0.001). At the Academic hospital, females were less likely to refuse the study than males (OR = 0.81, p = 0.01) and those not living in MUA/P's were less likely to refuse the study than those living in MUA/P's (OR = 0.81, p = 0.007). The most frequent barriers to enrollment included not being interested, being too busy, transportation, and illness. A lack of trust was reported less frequently. In conclusion, African-Americans can be readily recruited to pharmacogenetic clinical trials once contact has been successfully initiated. However, health care initiatives and increased recruitment efforts of subjects living in MUA/Ps are needed. Enrollment could be further enhanced by improving research awareness and knowledge of clinical trials, reducing time needed for participation, and compensating for travel.

Project description:Cardiovascular disease remains a leading cause of both morbidity and mortality worldwide. It is widely accepted that both concomitant medications (drug-drug interactions, DDIs) and genomic factors (drug-gene interactions, DGIs) can influence cardiovascular drug-related efficacy and safety outcomes. Although thousands of DDI and DGI (aka pharmacogenomic) studies have been published to date, the literature on drug-drug-gene interactions (DDGIs, cumulative effects of DDIs and DGIs) remains scarce. Moreover, multimorbidity is common in cardiovascular disease patients and is often associated with polypharmacy, which increases the likelihood of clinically relevant drug-related interactions. These, in turn, can lead to reduced drug efficacy, medication-related harm (adverse drug reactions, longer hospitalizations, mortality) and increased healthcare costs. To examine the extent to which DDGIs and other interactions influence efficacy and safety outcomes in the field of cardiovascular medicine, we review current evidence in the field. We describe the different categories of DDIs and DGIs before illustrating how these two interact to produce DDGIs and other complex interactions. We provide examples of studies that have reported the prevalence of clinically relevant interactions and the most implicated cardiovascular medicines before outlining the challenges associated with dealing with these interactions in clinical practice. Finally, we provide recommendations on how to manage the challenges including but not limited to expanding the scope of drug information compendia, interaction databases and clinical implementation guidelines (to include clinically relevant DDGIs and other complex interactions) and work towards their harmonization; better use of electronic decision support tools; using big data and novel computational techniques; using clinically relevant endpoints, preemptive genotyping; ensuring ethnic diversity; and upskilling of clinicians in pharmacogenomics and personalized medicine.

Dataset Information

Drug-gene and drug-drug interactions associated with tramadol and codeine therapy in the INGENIOUS trial.

Publications

Drug-gene and drug-drug interactions associated with tramadol and codeine therapy in the INGENIOUS trial.

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