Recently, using the patient’s genotype to guide warfarin dosing has gained interest; however, whether pharmacogenetics-based dosing (PD) improves clinical outcomes compared to conventional dosing (CD) remains unclear. Thus, we performed a meta-analysis to evaluate these two strategies.
The PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese VIP and Chinese Wan-fang databases were searched. The Cochrane Collaboration’s tool was used to assess the risk of bias in randomized controlled trials (RCTs). The primary outcome was time within the therapeutic range (TTR); the secondary end points were the time to maintenance dose and time to first therapeutic international normalized ratio (INR), an INR greater than 4, adverse events, major bleeding, thromboembolism and death from any cause.
A total of 11 trials involving 2,678 patients were included in our meta-analysis. The results showed that PD did not improve the TTR compared to CD, although PD significantly shortened the time to maintenance dose (MD = -8.80; 95% CI: -11.99 to -5.60; P<0.00001) and the time to first therapeutic INR (MD = -2.80; 95% CI: -3.45 to -2.15; P<0.00001). Additionally, PD significantly reduced the risk of adverse events (RR = 0.86; 95% CI: 0.75 to 0.99; P = 0.03) and major bleeding (RR = 0.36; 95% CI: 0.15 to 0.89, P = 0.03), although it did not reduce the percentage of INR greater than 4, the risk of thromboembolic events and death from any cause. Subgroup analysis showed that PD resulted in a better improvement in the endpoints of TTR and over-anticoagulation at a fixed initial dosage rather than a non-fixed initial dosage.
The use of genotype testing in the management of warfarin anticoagulation was associated with significant improvements in INR-related and clinical outcomes. Thus, genotype-based regimens can be considered a reliable and accurate method to determine warfarin dosing and may be preferred over fixed-dose regimens.
Trial Registration PROSPERO
Database registration: CRD42015024127.
Citation: Shi C, Yan W, Wang G, Wang F, Li Q, Lin N (2015) Pharmacogenetics-Based versus Conventional Dosing of Warfarin: A Meta-Analysis of Randomized Controlled Trials. PLoS ONE 10(12): e0144511. https://doi.org/10.1371/journal.pone.0144511
Editor: Francesca Borrelli, University of Naples Federico II, ITALY
Received: August 6, 2015; Accepted: November 19, 2015; Published: December 16, 2015
Copyright: © 2015 Shi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The authors gratefully acknowledge financial support from Zhejiang Provincial Program for the Cultivation of High-level Innovative Health Talents (2010-190-4, Nengming Lin). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Warfarin, a commonly used oral anticoagulant, has been proven to be effective in the treatment and prevention of thromboembolic events associated with atrial fibrillation (AF), deep vein thrombosis (DVT), pulmonary embolism (PE) and prosthetic heart valves ; however, warfarin’s narrow therapeutic window and inter- and intra-individual variability in dose requirements make warfarin dosing notoriously challenging in clinical practice [2,3]. Moreover, adverse events are common during the initial period of treatment before the maintenance dose is reached. Therefore, frequent monitoring of the patient’s international normalized ratio (INR) through periodic blood testing is warranted. Insufficient anticoagulation (INR lower than 2) increases the risk of thrombotic events, whereas overdosing (INR exceeding 3, particular above 4) confers a predisposition to bleeding [4,5].
Numerous physiological factors including age, body mass index, sex, race, dietary vitamin K intake and drug interactions are closely associated with warfarin dose requirement variations [6,7]. Although tremendous efforts have been made to improve warfarin dosing methods, no standardized regimen exists. During the last 10 years, research has shifted from a conventional dosing strategy to understanding the genetic factors of warfarin dosing. Indeed, several genes might be related to the activity and metabolism of warfarin, with the genotypes for cytochrome P450 2C9, CYP2C9 (related to the metabolism of S-warfarin) and the vitamin K epoxide reductase complex subunit 1 gene, VKORC1 (the molecular target of warfarin involved in the vitamin K cycle) gaining the most attention [8–11]. Recent data have suggested that warfarin dosing algorithms that combine genotypic information and clinical factors explain approximately half of the variation in the warfarin dose requirements [12–14]. These observations have raised interest in using genotype testing to guide the prescription of warfarin.
In recent years, a large number of genotype-based dosing models that incorporate genetic factors together with clinical characteristics have been developed; however, randomized controlled trials (RCTs) comparing pharmacogenetics-based dosing (PD) versus conventional dosing (CD) of warfarin have shown inconsistent outcomes. Thus, whether genotype-guided warfarin dosing can eventually improve clinical outcomes remains unclear. To address this issue, we performed a meta-analysis on all published RCTs to assess the effect of pharmacogenetics-based warfarin dosing in patients initiating warfarin therapy.
This systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (S1 PRISMA Checklist) . We systematically searched for unrestricted language articles included in the PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese VIP, and Chinese Wan-fang databases from inception to March 2015. The literature search in PubMed was carried out following the strategy shown in Table 1. The details of the strategy used in other databases were shown in S1 Appendix. Reference lists of the relevant studies were searched for additional literature.
To be eligible, original studies were required to meet all of the following criteria: (1) RCTs design; (2) included patients at least 18 years old with an indication for anticoagulation; (3) comparison of pharmacogenetics-based versus conventional dosing of warfarin; and (4) sufficient outcomes to allow for calculation of effect sizes. Exclusion criteria included the following: (1) non-RCT studies; (2) studies that included participants with a history of treatment with warfarin and known maintenance dose; and (3) studies without data from a comparison group.
Two investigators independently reviewed the full manuscripts of eligible articles, with each investigator blinded to the results of the other. The information extracted from each study included the first author, year of publication, study design, number of participants, patient characteristics (age, gender, race, indication), follow-up days, genotype (s) tested, warfarin dosing method, and outcomes. Any discrepancy was resolved through discussion.
Risk of bias assessment
Quality assessment of the selected RCTs was performed with the Cochrane Collaboration’s tool for assessing the risk of bias . This tool classifies studies as having a low, unclear, or high risk of bias across the following aspects: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other sources of bias.
The primary outcome was the time within the therapeutic range (TTR). The secondary outcomes were an INR greater than 4, time to maintenance dose and the first target INR, adverse events during anticoagulation treatment, the frequency of major bleeding, thromboembolic events, and death from any cause.
For dichotomous variables, the data were analyzed for a relative risk (RR) with 95% confidence intervals (CI) using the Mantel-Haenszel method. For continuous variables, the data were analyzed for the mean difference (MD) with a 95% CI using the inverse variance (IV) test. Fixed-effect or random-effect models were used for the meta-analysis, depending on the result of heterogeneity. Heterogeneity was explored using the I2 statistic. Significant heterogeneity existed for I2 > 50% . When heterogeneity was confirmed, a sensitivity analysis was undertaken by successively excluding the studies. Subgroup analysis was performed according to the type of conventional regimen (fixed-dose regimen or non-fixed initial doses regimen). Publication bias was evaluated visually by inspecting funnel plots and statistically using Egger’s test . All of the reported P-values were two-sided, with statistical significance set at 0.05. The statistical analyses were conducted using RevMan 5.3 (The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark).
Of the 1,460 articles found after the initial search, 11 studies involving 2,678 patients met the inclusion criteria [19–29]. The inclusion and exclusion of the RCTs for this meta-analysis are presented in a flow chart (Fig 1). The trials were mainly conducted across 5 countries: the USA (6 trials), China (3 trials), Israel (1 trial) and one multicenter trial (UK and Sweden). The patients tended to be middle-aged (median age: 59.7 years), with an approximately equal number of men and women (ratio of men to women: 1.1). Eight RCTs used CYP2C9 and VKORC1 genotype testing, two RCTs used CYP2C9 testing and one study used CYP2C9, VKORC1 and CYP4F2 testing. The follow-up periods ranged from 28 days to 3 months. The details of the study characteristics are summarized in Tables 2 and 3.
The risk of bias in the included studies
Randomization was performed in all of the included studies; however, only 6 studies appropriately described the sequence of generation. Most of the studies did not mention allocation concealment, apart from 4 trials. In most of the included RCTs, the participants and personnel were not blinded, corresponding to a high risk of bias. One study showed a high risk of bias in 3 items, and 4 RCTs showed a high risk of bias in 2 items. The risk of bias within the included trials is shown in Table 4.
Time within therapeutic range (TTR).
Nine of the trials [19–26,28] reported TTR data. We performed a random effects meta-analysis that included 1,148 participants in the PD group and 1,138 patients in the CD group. The genotype-guided treatment had no significant overall effect on the TTR in comparison to conventional warfarin dosing (MD = 4.26; 95% CI: -5.26 to 11.17; P = 0.08), with significant heterogeneity (I2 = 82%, P<0.00001). However, the subgroup analysis showed that the pharmacogenetics-based warfarin dosing group was associated with a higher percentage of TTR than the fixed-dose regimen arm (MD = 5.64; 95% CI: 0.36 to 10.91, P = 0.04), with significant heterogeneity (I2 = 58%, P = 0.05), but did not significantly differ from the non-fixed doses regimen arm (MD = 2.95; 95% CI: -5.26 to11.17; P = 0.48), with significant heterogeneity (I2 = 90%, P<0.00001) (Fig 2).
INR greater than 4.
A total of 8 trials [19–21,23–26,28] reported an INR greater than 4. We carried out a fixed effects meta-analysis that included 1,086 participants in the PD group and 1,075 patients in the CD group. The meta-analysis did not show a significant difference in the frequency of INR greater than 4 between the two arms (RR = 0.93; 95% CI: 0.81 to 1.06; P = 0.27), with a high consistency (I2 = 0%, P = 0.62). However, the subgroup analysis showed that the pharmacogenetics-guided group was associated with fewer incidences of INR greater than 4 when compared to the fixed-dose regimen group (RR = 0.79; 95% CI: 0.64 to 0.97; P = 0.02), with a high consistency (I2 = 0%, P = 0.92), but did not significantly differ from the non-fixed doses regimen group (RR = 1.05; 95% CI: 0.87 to 1.26; P = 0.62), with no statistical heterogeneity (I2 = 0%, P = 0.85) (Fig 3).
Time to maintenance dose and time to first therapeutic INR.
Six of the trials [21,22,25,27–29] reported on the time to maintenance dose. We carried out a random effects meta-analysis that included 618 participants in the PD group and 594 patients in the CD group. The genotype-guided treatment shortened the time to maintenance dose compared with the conventional regimen group (MD = -9.22; 95% CI: -14.55 to -3.88, P = 0.0007), with significant heterogeneity (I2 = 76%, P = 0.0007). The subgroup analysis showed that the time to maintenance dose of the patients in the PD arm was significantly shorter than the fixed warfarin dosing arm (MD = -8.80; 95% CI: -11.99 to -5.60; P<0.00001), with a high consistency (I2 = 0%, P = 0.38), but not significantly different from the non-fixed doses regimen group (MD = -7.66; 95% CI: -20.21 to 4.90; P = 0.23]), with significant heterogeneity (I2 = 88%, P = 0.0003) (Fig 4). Only two of the studies [20,22] provided the time to first target INR. These results showed that the time to first target INR of patients in the PD group was significantly shorter than that in the CD arm (MD = -2.80; 95% CI: -3.45 to -2.15; P<0.00001), with high consistency (I2 = 0%, P = 0.48) (Fig 5).
All of the included trials except one  reported on adverse events. We carried out a fixed effects meta-analysis that included 1,315 participants in the GD group and 1,304 patients in the CD group. The meta-analysis demonstrated that GD was associated with less adverse events compared with the control group (RR = 0.86; 95% CI: 0.75 to 0.99; P = 0.03), with high consistency (I2 = 0%, P = 0.31). The subgroup analysis showed that a reduction in the risk of adverse events was greater in the pharmacogenetics-based group than the fixed warfarin dosing group (RR = 0.82; 95% CI: 0.68 to 0.98; P = 0.03), with high consistency (I2 = 0%, P = 0.45); however, there was no difference between the pharmacogenetics-guided dosing group and the non-fixed dosing regimen group (RR = 0.91; 95% CI: 0.75 to 1.11; P = 0.34) (Fig 6).
Major bleeding, thromboembolism and all-cause mortality.
Five of the trials [21,22,25,26,28] reported major bleeding. The meta-analysis showed a significant reduction in the risk of major bleeding (RR = 0.36; 95% CI: 0.15 to 0.89, P = 0.03), with high consistency (I2 = 0%, P = 0.98) (Fig 7). A total of 5 studies reported on thromboembolism [21,23,25,26,28], and 4 of the studies [21,25,26,28] reported on all-cause mortality. However, there were no significant differences between treatment groups in terms of the frequency of thromboembolism (RR = 0.52; 95% CI: 0.21 to 1.24, P = 0.14) (Fig 8) and all-cause mortality (RR = 1.38; 95% CI: 0.54 to 3.49, P = 0.50), with no heterogeneity (Fig 9).
Sensitivity analysis and publication bias
We performed a sensitivity analysis to evaluate the stability of our pooled analysis by excluding the following studies: large trials (the largest trial in our study or subgroup) [26, 28]; small trials (<50 patients) [20, 23]; studies showing a high risk of bias ≥ 2 items [20, 21, 23, 27, 28]; trials including patients with heart valves mainly [24, 29] and the trial using CYP2C9, VKORC1 and CYP4F2 testing . The results indicated that the exclusion of these studies had not changed our primary outcomes (Table 5). Additionally, Egger’s test did not reveal significant evidence of publication bias.
Despite the fact that several models that combine clinical characteristics and genetic information have been shown to accurately predict warfarin doses, these models have not been incorporated into clinical practice because a direct clinical benefit associated with genotype-guided dosing has yet to be demonstrated. As noted in the Food and Drug Administration (FDA) warfarin label, a patient’s CYP2C9 and VKORC1 genotype information can assist in selecting the starting dose; however, the current guidelines of the American College of Chest Physicians (ACCP) recommend against genotype testing for guiding doses of warfarin until more evidence indicates a benefit . Furthermore, several insurance companies and healthcare providers have refused to pay for CYP2C9 and VKORC1 testing for warfarin dosing , making the application of genotype testing haphazard and only used in some specialist hospitals.
The present meta-analysis included 11 trials that investigated the efficacy and safety of genotype testing for warfarin dosing guidance. Due to the limited sample size of the published trials, the TTR was frequently used as the primary endpoint . In our study, the TTR was reported in 9 out of 11 trials. Although not statistically significant, we found a trend towards improvement of the percentage of TTR and INR greater than 4 in the genotype-guided group compared with the conventional regimen group.
The time to first target INR and maintenance dose can be used to mirror how quickly effective anticoagulation occurs and once a stable warfarin dose has been established, respectively. In our study, compared with clinical dosing of warfarin, pharmacogenetics-based dosing had significantly shortened the time to maintenance dose and time to first therapeutic INR.
To our knowledge, major bleeding, thromboembolism and adverse events are all clinical endpoints. The definitions of major bleeding and thromboembolism were those used in individual trials. We observed that the pharmacogenetics-based dosing of warfarin could be beneficial for the improvement of clinical endpoints, with a risk reduction for major bleeding by 64% and adverse events by 14%. Although not statistically significant, we found a trend towards a reduction in thromboembolism events in the genotype-guided group. A shortened TTR was likely to be the main mechanism responsible for the improvement of these clinical outcomes, and the lack of statistical significance for all-cause mortality may be due to the limited sample size.
Recently, several meta-analyses have reported the effects of pharmacogenetics- based warfarin dosing on clinical outcomes [42–46]. These meta-analyses have included different numbers of trials and participants, and thus the conclusions have been inconsistent. The first published meta-analysis of pharmacogenetics-based versus clinical dosing of warfarin with 3 RCTs observed no statistically significant difference in the hemorrhage rate and TTR . A previously published meta-analysis including 10 RCTs reported that genotype-based dosing presented some benefits. In particular, the authors found that genotype-based warfarin dosing increased the rate of TTR and reduced the risk for bleeding complications ; however, a non-randomized trial described by Lenzini PA et al.  was inappropriately included in this meta-analysis. A meta-analysis conducted by Franchini M et al.  including 2,812 patients indicated that pharmacogenetics-based initial vitamin K antagonist dosing is able to reduce major bleeding by approximately 50% compared with clinically based methods; however, their study included oral anticoagulants not limited to warfarin. Recently, a meta-analysis  including 10 RCTs showed that compared to warfarin therapy with a short time duration (within 1 month), long-time (>1 month) anticoagulation suggested a superior effect; however, a cohort study described by McMillin GA  was inappropriately included in this study. A meta-analysis conducted by Stergiopoulos K et al.  including 9 RCTs reported that a genotype-based dosing strategy did not result in a greater percentage of TTR, fewer patients with an INR greater than 4, or a reduction in major bleeding or thromboembolism events compared with conventional dosing of warfarin. However, this meta-analysis did not include any trials involving Chinese or East Asian patients as the main research subjects. Our study includes more Chinese patients than previous studies as shown above. These trials can help to evaluate the feasibility of genetics-based warfarin dosing in Chinese population.
We defines I2 >50% to represent significant heterogeneity. There are two endpoints (TTR and the percentage of INR greater than 4) represented significant heterogeneity. Other outcomes represented low heterogeneity (I2 = 0). In the subgroup analysis of the present study, genotype-based dosing was associated with a significant improvement in the rate of TTR compared with the fixed initial dose group but failed to show a significant difference compared to the non-fixed dosage group. The percentage of INR greater than 4 presented a similar result. We found that the pharmacogenetics-based arm was associated with an approximately 21% lower percentage of INR greater than 4 compared with the fixed-dose regimen. Therefore, we suggest that genotype-guided dosing should be applied rather than a fixed-dose regimen.
CYP4F2 was first identified as a contributor to warfarin dosing in Europeans, but without large effects or much compelling data . Only one trial using CYP4F2 testing described by Burmester JK et al.  was included in our meta-analysis. We performed a sensitivity analysis to evaluate the stability of our meta-analysis by excluding that trial, and no inconsistency results were revealed.
Although several new oral anticoagulants (dabigatran, apixaban, rivaroxaban, and most recently edoxaban) have been developed, warfarin will continue to be used and will likely remain a mainstay therapy for the following reasons: first, the long-term safety of these new oral anticoagulants remains unclear. Second, their application is limited or contraindicated under several circumstances. For instance, none of these new oral anticoagulants is approved for use during pregnancy or in babies and children. Additionally, new oral anticoagulants have not yet been applied in patients with mechanical prosthetic heart valves. Furthermore, no head-to-head trial between genotype-guided dosing of warfarin and new oral new oral anticoagulants has been performed, although this type of study should be conducted in the future.
There are several limitations to our study. First, to improve the quality of the data collected, only 11 RCTs were included in our study, although we identified a significant number of non-RCTs. Our study may also not be representative of patients seen in daily practice. Second, the RCTs in our review varied by population, length of follow-up, genotype-based and single clinical algorithm. The definitions of outcomes were also inconsistent across studies. Third, the largest trial in our study  contributed to almost 40% of the sample. In addition, the largest trial in the fixed-dose group reported by Pirmohamed et al.  contributed to almost 50% of the sample. These large trials may have induced bias in evaluating the endpoints in our study.
The authors gratefully acknowledge financial support from Zhejiang Provincial Program for the Cultivation of High-level Innovative Health Talents (2010-190-4, Nengming Lin). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Conceived and designed the experiments: NML. Performed the experiments: CCS WY GW FW QYL. Analyzed the data: CCS FW. Contributed reagents/materials/analysis tools: CCS WY GW. Wrote the paper: CCS QYL NML.
- 1. Hirsh J, Dalen J, Anderson DR, Poller L, Bussey H, Ansell J, et al. Oral anticoagulants: mechanism of action, clinical effectiveness, and optimal therapeutic range. Chest. 2001; 119:8S–21S. pmid:11157640
- 2. Burns M. Management of narrow therapeutic index drugs. J Thromb Thrombolysis. 1999;7: 137–43. pmid:10364779
- 3. Wadelius M, Pirmohamed M. Pharmacogenetics of warfarin: current status and future challenges. Pharmacogenomics J. 2007;7: 99–111. pmid:16983400
- 4. Pirmohamed M. Warfarin: almost 60 years old and still causing problems. Br J Clin Pharmacol. 2006;62: 509–11. pmid:17061959
- 5. Hylek EM. Complications of oral anti-coagulant therapy: bleeding and nonbleeding, rates and risk factors. Semin Vasc Med. 2003;3:271–8. pmid:15199460
- 6. Ageno W, Gallus AS, Wittkowsky A, Crowther M, Hylek EM, Palareti G, et al. Oral anticoagulant therapy: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest. 2012;141: e44S–88S. pmid:22315269
- 7. Holbrook AM, Pereira JA, Labiris R, McDonald H, Douketis JD, Crowther M, et al. Systematic overview of warfarin and its drug and food interactions. Arch Intern Med. 2005;165: 1095–106. pmid:15911722
- 8. Wadelius M, Chen LY, Eriksson N, Bumpstead S, Ghori J, Wadelius C, et al. Association of warfarin dose with genes involved in its action and metabolism. Hum Genet. 2007;121:23–34. pmid:17048007
- 9. Klein TE, Altman RB, Eriksson N, Gage BF, Kimmel SE, Lee MT, et al. Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J Med. 2009;360:753–64. pmid:19228618
- 10. Rieder MJ, Reiner AP, Gage BF, Nickerson DA, Eby CS, McLeod HL, et al. Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med. 2005;352: 2285–93. pmid:15930419
- 11. Voora D, Eby C, Linder MW, Milligan PE, Bukaveckas BL, McLeod HL, et al. Prospective dosing of warfarin based on cytochrome P-450 2C9 genotype. Thromb Haemost. 2005;93: 700–5. pmid:15841315
- 12. Carlquist JF, Horne BD, Muhlestein JB, Lappe DL, Whiting BM, Kolek MJ, et al. Genotypes of the cytochrome p450 isoform, CYP2C9, and the vitamin K epoxide reductase complex subunit 1 conjointly determine stable warfarin dose: a prospective study. J Thromb Thrombolysis. 2006;22:191–7. pmid:17111199
- 13. Sconce EA, Khan TI, Wynne HA, Avery P, Monkhouse L, King BP, et al. The impact of CYP2C9 and VKORC1 genetic polymorphisms and patient characteristics upon warfarin dose requirements: proposal for a new dosing regimen. Blood. 2005; 106:2329–33. pmid:15947090
- 14. Aquilante CL, Langaee TY, Lopez LM, Yarandi HN, Tromberg JS, Mohuczy D, et al. Influence of coagulation factor, vitamin K epoxide reductase complex subunit 1, and cytochrome P450 2C9 gene polymorphisms on warfarin dose requirements. Clin Pharmacol Ther. 2006;79: 291–302. pmid:16580898
- 15. Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6: e1000097. pmid:19621072
- 16. Higgins JP, Green S. Cochrane Handbook for Systematic Reviews of Interventions: John Wiley &Sons; 2011.
- 17. Higgins J, Thompson SG. Quantifying heterogeneity in a meta analysis. Statistics in medicine. 2002;21:1539–58. pmid:12111919
- 18. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629–34. pmid:9310563
- 19. Anderson JL, Horne BD, Stevens SM, Grove AS, Barton S, Nicholas ZP, et al. Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anticoagulation. Circulation. 2007;116:2563–70. pmid:17989110
- 20. Borgman MP, Pendleton RC, McMillin GA, Reynolds KK, Vazquez S, Freeman A, et al. Prospective pilot trial of PerMIT versus standard anticoagulation service management of patients initiating oral anticoagulation. Thromb Haemost. 2012;108:561–9. pmid:22836303
- 21. Burmester JK, Berg RL, Yale SH, Rottscheit CM, Glurich IE, Schmelzer JR, et al. A randomized controlled trial of genotype-based Coumadin initiation. Genet Med. 2011;13:509–18. pmid:21423021
- 22. Caraco Y, Blotnick S, Muszkat M. CYP2C9 genotype-guided warfarin prescribing enhances the efficacy and safety of anticoagulation: a prospective randomized controlled study. Clin Pharmacol Ther. 2008;83:460–70. pmid:17851566
- 23. Hillman MA, Wilke RA, Yale SH, Vidaillet HJ, Caldwell MD, Glurich I, et al. A prospective, randomized pilot trial of model-based warfarin dose initiation using CYP2C9 genotype and clinical data. Clin Med Res. 2005;3:137–45. pmid:16160068
- 24. Huang SW, Chen HS, Wang XQ, Huang L, Xu DL, Hu XJ, et al. Validation of VKORC1 and CYP2C9 genotypes on interindividual warfarin maintenance dose: a prospective study in Chinese patients. Pharmacogenet Genomics. 2009;19:226–34. pmid:19177029
- 25. Jonas DE, Evans JP, McLeod HL, Brode S, Lange LA, Young ML, et al. Impact of genotype-guided dosing on anticoagulation visits for adults starting warfarin: a randomized controlled trial. Pharmacogenomics. 2013;14:1593–603. pmid:24088130
- 26. Kimmel SE, French B, Kasner SE, Johnson JA, Anderson JL, Gage BF et al. A pharmacogenetic versus a clinical algorithm for warfarin dosing. N Engl J Med. 2013;369:2283–93. pmid:24251361
- 27. Li J, Liu S, Yang JH, Guo W, Wang ZZ, Chen Y, et al. A randomized controlled study of the VKORC1 and CYP2C9 genotypes in guiding warfarin therapy for pulmonary thromboembolism. Zhonghua Jie He He Hu Xi Za Zhi. 2013;36:950–53. pmid:24503429
- 28. Pirmohamed M, Burnside G, Eriksson N, Jorgensen AL, Toh CH, Nicholson T, et al. A randomized trial of genotype-guided dosing of warfarin. N Engl J Med. 2013;369:2294–303. pmid:24251363
- 29. Wang M, Lang X, Cui S, Fei K, Zou L, Cao J, et al. Clinical application of pharmacogenetic-based warfarin-dosing algorithm in patients of Han nationality after rheumatic valve replacement: a randomized and controlled trial. Int J Med Sci. 2012;9:472–9. pmid:22927772
- 30. Carlquist JF, Horne BD, Muhlestein JB, Lappé DL, Whiting BM, Kolek MJ, et al. Genotypes of the cytochrome p450 isoform, CYP2C9, and the vitamin K epoxide reductase complex subunit 1 conjointly determine stable warfarin dose: a prospective study. J Thromb Thrombolysis. 2006;22:191–7. pmid:17111199
- 31. Kovacs MJ, Rodger M, Anderson DR, Morrow B, Kells G, Kovacs J, et al. Comparison of 10-mg and 5-mg warfarin initiation nomograms together with low-molecular-weight heparin for outpatient treatment of acute venous thromboembolism. A randomized, double-blind, controlled trial. Ann Intern Med. 2003;138:714–19. pmid:12729425
- 32. Linder MW, Bon Homme M, Reynolds KK, Gage BF, Eby C, Silvestrov N, et al. Interactive modeling for ongoing utility of pharmacogenetic diagnostic testing: application for warfarin therapy. Clin Chem. 2009;55:1861–68. pmid:19679631
- 33. Ansell J, Hirsh J, Hylek E, Jacobson A, Crowther M, Palareti G, et al. Pharmacology and management of the vitamin K antagonists: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition). Chest. 2008;133:160S–198S. pmid:18574265
- 34. Ageno W, Johnson J, Nowacki B, Turpie AG. A computer generated induction system for hospitalized patients starting on oral anticoagulant therapy. Thromb Haemost. 2000;83:849–52. pmid:10896237
- 35. Hillman MA, Wilke RA, Caldwell MD, Berg RL, Glurich I, Burmester JK. Relative impact of covariates in prescribing warfarin according to CYP2C9 genotype. Pharmacogenetics. 2004;14:539–47. pmid:15284536
- 36. Gage BF, Eby C, Johnson JA, Deych E, Rieder MJ, Ridker PM, et al. Use of pharmacogenetic and clinical factors to predict the therapeutic dose of warfarin. Clin Pharmacol Ther. 2008;84:326–31. pmid:18305455
- 37. Lenzini P, Wadelius M, Kimmel S, Anderson JL, Jorgensen AL, Pirmohamed M, et al. Integration of genetic, clinical, and INR data to refine warfarin dosing. Clin Pharmacol Ther. 2010;87:572–8. pmid:20375999
- 38. Avery PJ, Jorgensen A, Hamberg AK, Wadelius M, Pirmohamed M, Kamali F, et al. A proposal for an individualized pharmacogenetics-based warfarin initiation dose regimen for patients commencing anticoagulation therapy. Clin Pharmacol. 2011; 90:701–71
- 39. Holbrook A, Schulman S, Witt DM, Vandvik PO, Fish J, Kovacs MJ, et al. Evidence based management of anticoagulant therapy: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence Based Clinical Practice Guidelines. Chest. 2012;141:152–84.
- 40. Meckley LM, Neumann PJ. Personalized medicine: factors influencing reimbursement. Health Policy. 2010;94:91–100. pmid:19815307
- 41. Furie B. Do pharmacogenetics have a role in the dosing of vitamin K antagonists? N Engl J Med. 2013;369:2345–6. pmid:24251364
- 42. Kangelaris KN, Bent S, Nussbaum RL, Garcia DA, Tice JA. Genetic testing before anticoagulation? A systematic review of pharmacogenetic dosing of warfarin. J Gen Intern Med. 2009;24:656–64. pmid:19306050
- 43. Tang Q, Zou H, Guo C, Liu Z. Outcomes of pharmacogenetics-guided dosing of warfarin: a systematic review and meta-analysis. Int J Cardiol. 2014;175:587–91. pmid:25005340
- 44. Franchini M, Mengoli C, Cruciani M, Bonfanti C, Mannucci PM. Effects on bleeding complications of pharmacogenetic testing for initial dosing of vitamin K antagonists: a systematic review and meta-analysis. J Thromb Haemost. 2014;12:1480–7. pmid:25040440
- 45. Li X, Yang J, Wang X, Xu Q, Zhang Y, Yin T. Clinical benefits of pharmacogenetic algorithm-based warfarin dosing: meta-analysis of randomized controlled trials. Thromb Res. 2015;135:621–9. pmid:25628141
- 46. Stergiopoulos K, Brown DL. Genotype-guided vs clinical dosing of warfarin and its analogues: meta-analysis of randomized clinical trials. JAMA Intern Med. 2014; 174:1330–1338. pmid:24935087
- 47. Lenzini PA, Grice GR, Milligan PE, Dowd MB, Subherwal S, Deych E, et al. Laboratory and clinical outcomes of pharmacogenetic vs. clinical protocols for warfarin initiation in orthopedic patients. J Thromb Haemost. 2008;6:1655–62. pmid:18662264
- 48. McMillin GA, Melis R, Wilson A, Strong MB, Wanner NA, Vinik RG, Gene-based warfarin dosing compared with standard of care practices in an orthopedic surgery population: a prospective, parallel cohort study. Ther Drug Monit. 2010;32:338–45. pmid:20386359
- 49. Donohue MM, Tirschwell DL. Implications of pharmacogenetic testing for patients taking warfarin or clopidogrel. Curr Neurol Neurosci Rep. 2011;11:52–60. pmid:21046289