a b s t r a c t

Background: CYP450 polymorphisms result in variable rates of drug metabolism. CYP drug-Drug interactions can contribute to altered drug effectiveness and safety.

Study objectives: The primary objective was to determine the percentage of emergency department (ED) patients with cytochrome 2C19 (CYP2C19) Drug-drug interactions. The secondary objective was to determine the preva- lence of CYP2C19 polymorphisms in a US ED population.

Methods: We conducted a prospective observational study in an Urban academic ED with 72,000 annual visits. drug ingestion histories for the 48 hours preceding ED visit were obtained; each drug was coded as CYP2C19 sub- strate, inhibitor, inducer, or not CYP2C19 dependent. Ten percent of patients were randomized to undergo CYP2C19 genotyping using the Roche Amplichip.

Results: A total of 502 patients were included; 61% were female, 65% were white, and median age was 39 years (interquartile range, 22-53). One hundred thirty-one (26.1%) patients had taken at least 1 CYP2C19-dependent home drug. Eighteen (13.7%) patients who were already taking a CYP2C19-dependent drug were given or pre- scribed a CYP2C19-dependent drug while in the ED. Among the 53 patients genotyped, 52 (98%) were extensive metabolizers and 1 was a poor metabolizer.

Conclusions: In a population of ED patients, more than a quarter had taken a CYP2C19-dependent drug in the pre- ceding 48 hours, but few were given or prescribed another CYP2C19-dependent drug in the ED. On genotyping analysis, CYP2C19 polymorphisms were uncommon in our cohort. We conclude that changing prescribing prac- tice due to CYP2C19 drug-drug interaction or genotype is unlikely to be useful in most US ED populations.

(C) 2015

Introduction

Cytochrome P450 (CYP450) polymorphisms result in variable rates of drug metabolism. This has important implications for drug effective- ness and safety [1]. Hepatic cytochrome 2C19 (CYP2C19), a CYP450 sub- type, metabolizes up to 15% of known pharmaceuticals [2] including drugs with narrow therapeutic windows frequently encountered by physicians such as warfarin, clopidogrel, and carbamazepine (Table 1). CYP2C19 enzyme phenotypes are classified as poor metabolizer,

? Meetings: These data were presented at SAEM in May 2015, San Diego, CA, and at ACMT in March 2015, Clearwater Beach, FL.

?? Disclosures: Labcorp Inc provided the Roche Amplichip for genotyping in this study.

This work was supported in part by the National Institutes of Health grants K23 GM110516 and CTSA UL TR001082.

? Author contributions: AAM conceived the study, designed the trial, and obtained re-

search funding. JC and LH were responsible for data collection and manuscript revision. AAM, HSK, and HKF are responsible for the data analysis and interpretation. HKF drafted the manuscript. HSK and AAM contributed substantially to its revision.

* Corresponding author at: Leprino Bldg, 7th Floor Campus Box B-215, 12401 E 17th Ave, Aurora, CO, 80045. Tel.: +1 720 848 6776; fax: +1 720 848 7374.

E-mail address: andrew.monte@ucdenver.edu (A.A. Monte).

intermediate metabolizer, extensive (normal) metabolizer, and ultra- rapid metabolizer depending upon the patient’s underlying genetic polymorphisms [3]. Commercially available genotype assays identify poor metabolizers and extensive metabolizers through identification of a variable number of gene polymorphisms [4].

Genotyping for specific polymorphisms is increasingly recommend- ed by the Food and Drug Administration before instituting drug therapy [5]. There are a number of drugs where genotyping can predict adverse drug events, drug effectiveness, or therapeutic failure [6]. These drugs include abacavir [7,8], clopidogrel [9], and tamoxifen [10]. In addition, genotyping for glucose-6-phosphate deficiency before prescribing of certain hemolytic drugs is advised [11,12]. The National Comprehensive Cancer Network recommends genotyping for certain tumor genes asso- ciated with improved chemotherapeutic efficacy before initiation of therapy [13]. Knowledge of patient genotypes in the emergency depart- ment (ED) may lead to improved efficacy and safety of drugs prescribed in the near future. However, genotyping is not sufficient to predict safe- ty and effectiveness [14], and accounting for clinical factors such as drug-drug interaction may be equally important [1,15]. Therefore, char- acterizing the frequency of drug-drug interactions and the prevalence of

http://dx.doi.org/10.1016/j.ajem.2015.10.055

0735-6757/(C) 2015

Table 1

CYP2C19-dependent drugs used in EDs

Drug/drug class Related emergency condition Role of CYP2C19

Warfarin Venous thrombosis, pulmonary

embolism, atrial fibrillation

Clopidogrel Acute coronary syndrome, myocardial infarction, recent stroke

Primarily metabolized by CYP2C9, although inhibition of CYP2C19 may result in elevated INR.

Dependent on CYP2C19 for conversion to active metabolite.

proton pump inhibitors (PPIs): esomeprazole, lansoprazole, omeprazole, pantoprazole

Antiepileptics: diazepam, phenytoin, S-mephenytoin, phenobarbitone, oxcarbazepine

Ulcers, gastroesophageal reflux disease Most PPIs are inhibitors of CYP2C19 which can affect effectiveness of

concurrently administered CYP2C19-dependent drugs. Epilepsy, other seizure disorders Inhibition of CYP2C19 may lead to antiepileptic toxicity.

Antimicrobials: isoniazid, voriconazole Bacterial or fungal infection Isoniazid is an inhibitor of CYP2C19 which can affect effectiveness of

concurrently administered CYP2C19-dependent drugs.

Antidepressants: citalopram, amitriptyline Depression, anxiety, and other

psychological disorders

Inhibition of this enzyme may lead to serotonin or cardiovascular toxicity due to excess parent drug.

genetic polymorphisms in an ED population allows for an estimation of the implications for drug-gene interaction in ED patients [1,16].

Drug-gene interactions are especially important with the CYP2C19 enzyme which is responsible for metabolism of many clinically perti- nent drugs in the ED. Pharmacokinetic differences have been demon- strated between CYP2C19 genotype subgroups for several drugs [3] including proton pump inhibitors [17], sedatives [18], anticonvulsants [19], antidepressants [20], and antimicrobials [21,22]. Metabolism of these drugs varies considerably from extensive metabolizers to poor metabolizers. Poor metabolizer prevalence varies by race. A total of 12%-23% of Asians [23-25], 1%-6% of whites [26-28], and 1%-7.5% of Africans [29] are classified as CYP2C19 poor metabolizers. Identification of drug-gene and pairing this information with drug-drug interaction data may alter the way ED physicians prescribe CYP2C19-dependent drugs. We have chosen to focus on CYP2C19 because of the high poten- tial for interactions with narrow therapeutic drugs. In addition, many of these drugs are metabolized almost exclusively through this pathway, with no redundancy, raising the potential for clinically significant inter- actions. The primary objective was to determine the percentage of ED patients with CYP2C19 Drug-drug interactions. The secondary objec- tives were to determine the prevalence of CYP2C19 polymorphisms in a US ED population and to determine if genotyping and identification of drug-drug interactions for CYP2C19 could reasonably alter drug ther- apy by ED physicians.

Materials and methods

Patients and study design

This was a prospective observational cohort gathered in a large urban academic US ED with approximately 72,000 patient visits per year. The study enrollment procedures are described in the parent trial (Clinical Trials # NCT01859715) [15]. In brief, subjects were includ- ed if they self-reported pain or nausea during the initial nursing assess- ment. Patients were excluded if they were younger than 18 years, unable to speak English, or previously diagnosed with chronic pain or cyclic vomiting. In addition, those with measured or known glomerular filtration rate of b 60 mL/(min 1.73 m²) or those with acute altered men- tal status were excluded. In patients with dementia or critical illness, the drug ingestion history was reconciled with the health care proxy. Pa- tients were approached after triage, after nurse drug reconciliation, and after initial stabilization when the patient arrived by ambulance. The local institutional review board approved the study, and all subjects provided written informed consent.

Drug ingestion histories

Detailed drug histories for the 48 hours preceding the ED visit were obtained by the principal investigator or a professional research assis- tant (JC) trained in identical methods. All prescription drugs,

nonprescription drugs, vitamins, herbals, and supplement drugs were captured along with the dose and time since the patient’s last dose. Drug histories were gathered in a structured format. Initially, we asked, “what medications have you taken in the last 48 hours?” We then asked specifically about the use of prescription drugs, nonprescrip- tion drugs, vitamins, herbals, or traditional drugs, and dietary supple- ments. All reported drugs were recorded. When available, Pill bottles were obtained to verify drug doses. If the patient had difficulty recalling the prescription name, their pharmacy was contacted to ensure accura- cy of the obtained history. Over-the-counter nonprescription combina- tion formulations were reconciled using Internet pictures to verify the specific product ingested. The ED medical record was abstracted manu- ally, and medications administered in the ED or prescribed at ED dis- charge were recorded. Patient demographic details were also abstracted from the ED medical record (Table 2).

Interaction identification

All patient-reported drugs were categorized as a CYP2C19 substrate, inhibitor, inducer, or not CYP2C19 dependent using the University of Indiana CYP450 Interaction Table [30]. The presence of CYP2C19 inter- action was considered dichotomous; interaction was present if the sub- ject had taken a home CYP2C19-dependent drug and was administered or prescribed a CYP2C19-dependent drug in the ED. We considered clin- ically significant drug-drug interactions to include drugs with narrow therapeutic windows. Those drugs included warfarin, clopidogrel, car- bamazepine, oxcarbazepine, and topiramate.

Genotyping

Fifty-three patients were randomized for CYP2C19 genotyping by a random number generator. Genotyping was provided by LabCorp using the CYP2D6/2C19 Amplichip. Genotyping with the Amplichip ac- counts for 3 distinct CYP2C19 polymorphisms categorizing the individ- ual’s genotype into 1 of 3 predicted metabolizer groups: poor metabolizer, intermediate metabolizer, or extensive metabolizer [31].

Table 2

Patient demographics

Demographic variable	Total cohort, N = 502	Genotyped cohort, n= 53
Age, y (range, IQR)	39 (18-89, 22-53.3)	51 (20-85, 33-63.5)
Male, n (%)	198 (39.4)	23 (43.4)
Ethnicity/race Hispanic/Latino, n (%)	98 (19.5)	17 (32.1)

White, n (%) 326 (64.9) 40 (75.5)

African American, n (%) 162 (32.3) 11 (20.8)

Asian, n (%) 9 (1.8) 0

American Indian/Alaskan Native, n (%)	19 (3.8)	2 (3.8%)
Native Hawaiian/Pacific Islander, n (%)	6 (1.2)	0
Median no. of drugs taken (range, IQR)	3 (0-33, 1-6)	5 (1-17, 3-11)

Fig. 1. Patient flow through enrollment and analysis.

Outcomes

The primary outcome of this study was the prevalence of CYP2C19 drug-drug interaction. The secondary outcomes were the prevalence of CYP2C19 polymorphisms and the presence of drug-gene interactions.

Data analysis

Descriptive statistics were used to characterize demographic data, the frequency of patients taking a CYP2C19-dependent drug, and the frequency of CYP2C19 drug-drug interactions in the study population. JMP 10 was used for data analysis.

Results

Characteristics of study subjects

A total of 502 of 655 (76.6%) approached patients consented to en- rollment. The overall demographics of the sample were representative of the ED population during the sampling period (Table 2). A total of 286 (56.9%) of consented patients were enrolled through triage; the re- mainder were enrolled in the ED after initial stabilization or after ambu- lance arrival (Fig. 1).

Drug histories

The median number of home drugs taken by patients in the 48 hours before ED presentation was 3 (range, 0-33; interquartile range [IQR], 1- 6). A total of 131 of the 502 subjects (26.1%) enrolled had taken at least 1 CYP2C19-dependent drug in the 48 hours before ED presentation (Fig. 1). Of these, 117 (88.6%) had taken substrates, 22 (16.6%) had taken inhibitors, and 0 had taken an inducer.

CYP2C19 drug-drug interactions

Eighteen of the 131 subjects (13.7%) on a CYP2C19 were given an- other CYP2C19-dependent drug in the ED (Fig. 2). Of the 502 subjects enrolled, 18 (3.6%) subjects could have had a CYP2C19 drug-drug inter- action. Twenty-nine (5.8%) patients were on home drugs with a narrow therapeutic window. There were 5 (1.0%) subjects with clinically signif- icant CYP2C19 interactions due to drugs given or prescribed in the ED: a patient on topiramate was given prednisone, 1 patient on escitalopram

was prescribed warfarin, 1 patient on pantoprazole was prescribed war- farin, another on both pantoprazole and sertraline was prescribed war- farin, and a patient on omeprazole was prescribed both warfarin and prednisone. No patients taking carbamazepine or oxcarbazepine were given or prescribed CYP2C19 drugs in the ED.

Genotyping

Fifty-three subjects were genotyped for CYP2C19 metabolizer status. Of the 53, a total of 52 (98%) were extensive metabolizers and 1 (2%) was a poor metabolizer. The one poor metabolizer was American Indian/Alaskan Native, was taking esomeprazole at home, and did not receive a CYP2C19 drug or prescription in the ED.

Discussion

In a cohort of ED patients presenting with pain or nausea, more than a quarter of patients reported taking a CYP2C19-dependent drug in the 48 hours preceding their visit. Although some CYP2C19 drugs have nar- row therapeutic windows (eg, topiramate, warfarin, clopidogrel), only 6% of patients in our ED population were taking these drugs, and only 1% of those were given or prescribed a CYP2C19-interacting drug. Of those with a clinically significant drug-drug interaction, 80% involved warfarin and would be followed with regular prothrombin time moni- toring, mitigating potential adverse drug events (ADEs). On genotyping analysis, the prevalence of CYP2C19 polymorphisms was low. There- fore, given that the likelihood of a clinically significant CYP2C19 drug- drug or drug-gene interactions is low, CYP2C19 genotyping, as currently available, is unlikely to be useful in an ED population.

Drug-drug interactions alter drug effectiveness and safety. Emergen- cy physicians must consider the possibility of drug interactions when choosing therapies in patients taking drugs with narrow therapeutic windows. Many oral contraceptives are known to be inhibitors of CYP2C19. As of 2015, the CDC reports that 17% of women aged 15-44 in the United States take oral contraceptives [32]. We did not identify significant interaction with women taking oral contraceptives in this co- hort. However, this population may be of interest to physicians in the future when prescribing antiepileptics or drugs such as clopidogrel that rely on CYP2C19 to produce the pharmacologically active metabolite. Topiramate, carbamazepine, and oxcarbazepine are listed as Class D (evidence of human fetal risk) in pregnancy. Thus, when a physician prescribes one of these drugs, it may be advisable to discuss

Fig. 2. Proportion of patients taking, given, or prescribed a CYP2C19-dependent drug.

contraceptive choice with the patient and consider potential drug inter- actions. Estradiol, however, is not metabolized through this pathway, mitigating the risk of Stent thrombosis in those on concomitant hor- mone replacement therapy and clopidogrel.

As demonstrated by the failures of pharmacogenetic prediction for warfarin [33,34] and clopidogrel therapy [9], it is unclear that genotyp- ing CYP2C19 improves clinically significant outcomes. It is estimated that 7.3% of the general population has clinically actionable CYP2C19 ge- notypes [35]; yet only 2% of our study population had a polymorphism, and only 26% of patients reported taking a CYP2C19-dependent drug 48 hours before ED arrival. This resulted in less than a 1% drug-gene inter- action in our cohort. Genotyping costs approximately $500 for the com- mercially available Roche Ampliship [36]; thus, genotyping CYP2C19 in ED patients is unlikely to be cost-effective at our institution.

Although not currently cost-effective, the cost of genetic testing con- tinues to decline. Adverse drug events are among the most costly iatro- genic diseases [37], and some ADEs may be avoided if P450 genotypes are known (ie, opiate toxicity in patients taking codeine [38] or hypersensitivity associated with carbamazepine therapy [39]). Pharmacogenomic testing is currently recommended for several drugs commonly encountered by emergency physicians [6]. Predicting drug response before initiation of a new drug could result in fewer therapeu- tic failures, less recidivism for a persistent condition, and fewer ADEs. Patients and providers desire more precision in drug therapy, and genotyping represents a tool to achieve this goal. Although attempts at predicting a patient’s response based on genotype alone have largely been unsuccessful [33,34], accounting for drug-drug interaction has shown some promise in prediction of pharmacokinetics/pharmacody- namics [32,40] of drugs in the ED. The combination of genetics and clin- ical factors such as drug-drug interaction may improve the prediction of drug effectiveness [1,15]. Prospective studies are needed to demon- strate the utility of these approaches in the ED.

Limitations

These data are limited by the nature of self-reported drug ingestion histories. Emergency department physicians must rely on these histo- ries for all drug therapy decisions; thus, this method is reflective of true clinical practice. We included patients with chest pain, thus captur- ing patients that may have been taking clopidogrel, and patients with gastritis are frequently prescribed proton pump inhibitors (CYP2C19 dependent) in our ED. Therefore, we have conservatively biased the re- sults toward identifying more interactions than may be present overall. Exclusion of non-English-speaking patients may influence the distribu- tion of the underlying CYP2C19 subgroups. Certain races are known to have a higher prevalence of some CYP2C19 polymorphisms associated

with altered metabolic activity. Thus, the external validity of this study is limited by the low percentage (1.8%) of patients with Asian descent in the cohort, consistent with our overall ED demographics, and no Asians were genotyped. Emergency departments with a higher Asian patient population would likely demonstrate a higher poor metabolizer prevalence. The parent trial enrolled patients with pain, nausea, or vomiting. These chief complaints may affect the ultimate drug therapy and thus alter the number of drug-drug interactions identified. Howev- er, pain, nausea, and vomiting are the most common chief complaints in our ED overall, suggesting that this population is representative of our overall ED population.

Conclusions

In a population of ED patients, more than a quarter had taken a CYP2C19-dependent drug in the preceding 48 hours, but few were given or prescribed another CYP2C19-dependent drug in the ED. On genotyping analysis, CYP2C19 polymorphisms were uncommon in our cohort. In summary, our findings suggests that genotyping of CYP2C19 is not well suited to the ED.

References

1. Monte AA, Heard KJ, Vasiliou V. Prediction of drug response and safety in clinical practice. J Med Toxicol 2012;8:43-51.
2. Guengerich FP. Cytochrome P450s and other enzymes in drug metabolism and tox- icity. AAPS J 2006;8:E101-11.
3. Desta Z, Zhao X, Shin JG, Flockhart DA. Clinical significance of the cytochrome P450 2C19 genetic polymorphism. Clin Pharmacokinet 2002;41:913-58.
4. Scott SA, Sangkuhl K, Gardner EE, Stein CM, Hulot JS, Johnson JA, et al. Clinical Phar- macogenetics Implementation Consortium guidelines for cytochrome P450-2C19 (CYP2C19) genotype and clopidogrel therapy. Clin Pharmacol Ther 2011;90:328-32.
5. FDA Drug Safety Communication. Reduced effectiveness of Plavix (clopidogrel) in patients who are poor metabolizers of the drug. http://www.fda.gov/Drugs/ DrugSafety/PostmarketDrugSafetyInformationforPatientsandProviders/ucm203888. htm; 2010.
6. CPIC genes/drugs. PharmGKB. Accessed March 3, 2015. https://www.pharmgkb.org/ cpic/pairs.
7. Kapoor R, Martinez-Vega R, Dong D, Tan SY, Leo YS, Lee CC, et al. Reducing hypersen- sitivity reactions with HLA-B*5701 genotyping before abacavir prescription: clinical- ly useful but is it cost-effective in Singapore? Pharmacogenet Genomics 2015;25: 60-72.
8. Mallal S, Phillips E, Carosi G, Molina JM, Workman C, Tomazic J, et al. HLA-B*5701 screening for hypersensitivity to abacavir. N Engl J Med 2008;358:568-79.
9. Holmes MV, Perel P, Shah T, Hingorani AD, Casas JP. CYP2C19 genotype, clopidogrel metabolism, Platelet function, and cardiovascular events: a systematic review and meta-analysis. JAMA 2011;306:2704-14.
10. Jung JA, Lim HS. Association between CYP2D6 genotypes and the clinical outcomes of adjuvant tamoxifen for breast cancer: a meta-analysis. Pharmacogenomics 2014;15:49-60.
11. Luzzatto L, Seneca E. G6PD deficiency: a classic example of pharmacogenetics with on-going clinical implications. Br J Haematol 2014;164:469-80.
12. Minucci A, Giardina B, Zuppi C, Capoluongo E. Glucose-6-phosphate dehydrogenase laboratory assay: How, when, and why? IUBMB Life 2009;61:27-34.
13. Carlson RW. Industry “rewrites” of NCCN Guidelines. J Natl Compr Canc Netw 2011;9:257.
14. Dunnenberger HM, Crews KR, Hoffman JM, Caudle KE, Broeckel U, Howard SC, et al. Preemptive clinical pharmacogenetics implementation: current programs in five US medical centers. Annu Rev Pharmacol Toxicol 2015;55:89-106.
15. Monte AA, Heard KJ, Campbell J, Hamamura D, Weinshilboum RM, Vasiliou V. The effect of CYP2D6 drug-drug interactions on hydrocodone effectiveness. Acad Emerg Med 2014;21:879-85.
16. Nebert DW, Jorge-Nebert L, Vesell ES. Pharmacogenomics and “individualized drug therapy”: high expectations and disappointing achievements. Am J Pharmacogenomics 2003;3:361-70.
17. Zvyaga T, Chang SY, Chen C, Yang Z, Vuppugalla R, Hurley J, et al. Evaluation of six proton pump inhibitors as inhibitors of various human cytochromes P450: focus on cytochrome P450 2C19. Drug Metab Dispos 2012;40:1698-711.
18. Jung F, Richardson TH, Raucy JL, Johnson EF. Diazepam metabolism by cDNA- expressed human 2C P450s: identification of P4502C18 and P4502C19 as low K(M) diazepam N-demethylases. Drug Metab Dispos 1997;25:133-9.
19. Soskin DP, Kane AJ, Stern TA. Phenytoin toxicity secondary to an oxcarbazepine-phe- nytoin 2C19 interaction. Psychosomatics 2010;51:532-5.
20. Koyama E, Chiba K, Tani M, Ishizaki T. Reappraisal of human CYP isoforms involved in imipramine N-demethylation and 2-hydroxylation: a study using microsomes ob- tained from putative extensive and poor metabolizers of S-mephenytoin and eleven recombinant human CYPs. J Pharmacol Exp Ther 1997;281:1199-210.
21. Wen X, Wang JS, Neuvonen PJ, Backman JT. Isoniazid is a mechanism-based inhibitor of cytochrome P450 1A2, 2A6, 2C19 and 3A4 isoforms in human liver microsomes. Eur J Clin Pharmacol 2002;57:799-804.
22. Desta Z, Soukhova NV, Flockhart DA. Inhibition of cytochrome P450 (CYP450) iso- forms by isoniazid: potent inhibition of CYP2C19 and CYP3A. Antimicrob Agents Chemother 2001;45:382-92.
23. Nakamura K, Goto F, Ray WA, McAllister CB, Jacqz E, Wilkinson GR, et al. Interethnic differences in genetic polymorphism of debrisoquin and mephenytoin hydroxylation between Japanese and CaucAsian populations. Clin Pharmacol Ther 1985;38:402-8.
24. Jurima M, Inaba T, Kadar D, Kalow W. Genetic polymorphism of mephenytoin p(4′)- hydroxylation: difference between Orientals and Caucasians. Br J Clin Pharmacol 1985;19:483-7.
25. Bertilsson L, Lou YQ, Du YL, Liu Y, Kuang TY, Liao XM, et al. Pronounced differences between native Chinese and Swedish populations in the polymorphic hydroxyl- ations of debrisoquin and S-mephenytoin. Clin Pharmacol Ther 1992;51:388-97.
26. Xie HG, Stein CM, Kim RB, Wilkinson GR, Flockhart DA, Wood AJ. Allelic, genotypic and phenotypic distributions of S-mephenytoin 4′-hydroxylase (CYP2C19) in

    healthy Caucasian populations of European descent throughout the world. Pharma- cogenetics 1999;9:539-49.

    Bertilsson L. Geographical/interracial differences in polymorphic drug oxidation. Current state of knowledge of cytochromes P450 (CYP) 2D6 and 2C19. Clin Pharmacokinet 1995;29:192-209.

27. Goldstein JA, Ishizaki T, Chiba K, de Morais SM, Bell D, Krahn PM, et al. Frequencies of the defective CYP2C19 alleles responsible for the mephenytoin poor metabolizer phenotype in various Oriental, Caucasian, Saudi Arabian and American black popu- lations. Pharmacogenetics 1997;7:59-64.
28. Xie HG, Kim RB, Stein CM, Wilkinson GR, Wood AJ. Genetic polymorphism of (S)- mephenytoin 4′-hydroxylation in populations of African descent. Br J Clin Pharmacol 1999;48:402-8.
29. Flockhart D. Drug Interactions: Cytochrome P450 Drug Interaction Table. Indiana Univer- sity School of Medicine; 2007. [http://medicine.iupui.edu/clinpharm/ddis/table.aspx].
30. Amplichip P450 CYP test. Accessed March 3, 2015. http://molecular.roche.com/assays/ Pages/AmpliChipCYP450Test.aspx.
31. Contraceptive use. Centers for Disease Control and Prevention. (Accessed March 3, 2015, at http://www.cdc.gov/nchs/fastats/contraceptive.htm).
32. Kimmel SE, French B, Kasner SE, Johnson JA, Anderson JL, Gage BF, et al. A pharmacoge- netic versus a clinical algorithm for warfarin dosing. N Engl J Med 2013;369:2283-93.
33. Verhoef TI, Ragia G, de Boer A, Barallon R, Kolovou G, Kolovou V, et al. A randomized trial of genotype-guided dosing of acenocoumarol and phenprocoumon. N Engl J Med 2013;369:2304-12.
34. Strom CM, Goos D, Crossley B, Zhang K, Buller-Burkle A, Jarvis M, et al. Testing for variants in CYP2C19: population frequencies and testing experience in a clinical lab- oratory. Genet Med 2012;14:95-100.
35. Nakamoto K, Kidd JR, Jenison RD, Klaassen CD, Wan YJ, Kidd KK, et al. Genotyping and haplotyping of CYP2C19 functional alleles on thin-film biosensor chips. Pharmacogenet Genomics 2007;17:103-14.
36. Gurwitz JH, Field TS, Harrold LR, Rothschild J, Debellis K, Seger AC, et al. Incidence and preventability of adverse drug events among older persons in the ambulatory setting. JAMA 2003;289:1107-16.
37. Koren G, Cairns J, Chitayat D, Gaedigk A, Leeder SJ. Pharmacogenetics of morphine poisoning in a breastfed neonate of a codeine-prescribed mother. Lancet 2006; 368:704.
38. McCormack M, Alfirevic A, Bourgeois S, Farrell JJ, Kasperaviciute D, Carrington M, et al. HLA-A*3101 and carbamazepine-induced hypersensitivity reactions in Euro- peans. N Engl J Med 2011;364:1134-43.
39. Parker RB, Soberman JE. Effects of paroxetine on the pharmacokinetics and pharma- codynamics of immediate-release and extended-release metoprolol. Pharmacother- apy 2011;31:630-41.