Randomized Trial of Genotype-Guided Versus Standard Warfarin Dosing in Patients Initiating Oral Anticoagulation

Anderson, Jeffrey L.; Horne, Benjamin D.; Stevens, Scott M.; Grove, Amanda; Barton, Stephanie; Nicholas, Zachery P.; Kahn, Samera F.S.; May, Heidi T.; Samuelson, Kent M.; Muhlestein, Joseph B.; Carlquist, John F.

doi:10.1161/circulationaha.107.737312

Cited by 630 publications

(515 citation statements)

References 37 publications

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“…Algorithms were selected based on the following criteria: the algorithms that included nongenetic or genetic variables not available in our study, and included only a minority of clinical variables, and were based on relatively small clinical populations were excluded; algorithms that were derived from Asian with the consideration of race of each algorithm made up of at least 15% Asians in original populations, and algorithms validated best in Asians were included. This process identified eight algorithms [12][13][14][15][16][17][18][19]. The characteristics and equations of selected algorithms are listed in Supporting Information Tables II and III. Collection of subjects and clinical data.…”

Section: Methodsmentioning

confidence: 99%

“…In the interest of determining an accurate predictive pharmacogenetic algorithm to promote rational treatment, especially for Chinese outliers, we attempted to assess the predictive ability of published warfarin pharmacogenetic dosing algorithms in Mainland Han Chinese [12][13][14][15][16][17][18][19].…”

Section: Accuracy Assessment Of Pharmacogenetic Algorithms For Warfarmentioning

confidence: 99%

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Accuracy assessment of pharmacogenetic algorithms for warfarin dose prediction in Chinese patients

Guo

Sun

et al. 2012

American J Hematol

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Section: Methodsmentioning

confidence: 99%

Section: Accuracy Assessment Of Pharmacogenetic Algorithms For Warfarmentioning

confidence: 99%

Accuracy assessment of pharmacogenetic algorithms for warfarin dose prediction in Chinese patients

Guo

Sun

et al. 2012

American J Hematol

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Section: Background and Significancementioning

confidence: 99%

“…This is particularly true with warfarin due to additional factors, such as diet, concurrent medications, and medical indication that alter dosing requirements. These factors complicate prescribers' decisions, especially on how to dose the medication and make it difficult to further assess the impact of genetic information [24].While some CDSS assessments have applied pharmacogenomics, these were often limited in scope and generally did not recommend a specific dose [25,26]. To develop CDSS interfaces, a number of methods have been identified.…”

mentioning

confidence: 99%

Iterative Development and Evaluation of a Pharmacogenomic-Guided Clinical Decision Support System for Warfarin Dosing

Melton¹,

Zillich²,

Saleem³

et al. 2016

Appl Clin Inform

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SummaryObjective: Pharmacogenomic-guided dosing has the potential to improve patient outcomes but its implementation has been met with clinical challenges. Our objective was to develop and evaluate a clinical decision support system (CDSS) for pharmacogenomic-guided warfarin dosing designed for physicians and pharmacists. Methods: Twelve physicians and pharmacists completed 6 prescribing tasks using simulated patient scenarios in two iterations (development and validation phases) of a newly developed pharmacogenomic-driven CDSS prototype. For each scenario, usability was measured via efficiency, recorded as time to task completion, and participants' perceived satisfaction which were compared using Kruskal-Wallis and Mann Whitney U tests, respectively. Debrief interviews were conducted and qualitatively analyzed. Usability findings from the first (i.e. development) iteration were incorporated into the CDSS design for the second (i.e. validation) iteration. Results: During the CDSS validation iteration, participants took more time to complete tasks with a median (IQR) of 183 (124-247) seconds versus 101 (73.5-197) seconds in the development iteration (p=0.01). This increase in time on task was due to the increase in time spent in the CDSS corresponding to several design changes. Efficiency differences that were observed between pharmacists and physicians in the development iteration were eliminated in the validation iteration. The increased use of the CDSS corresponded to a greater acceptance of CDSS recommended doses in the validation iteration (4% in the first iteration vs. 37.5% in the second iteration, p<0.001). Overall satisfaction did not change statistically between the iterations but the qualitative analysis revealed greater trust in the second prototype. Conclusions: A pharmacogenomic-guided CDSS has been developed using warfarin as the test drug. The final CDSS prototype was trusted by prescribers and significantly increased the time using the tool and acceptance of the recommended doses. This study is an important step toward incorporating pharmacogenomics into CDSS design for clinical testing. Research ArticleBL Background And SignificancePersonalized medicine is an emerging field with the fundamental objective to predict a patient's response in order to individualize drug therapy for improved medication effectiveness and safety. Pharmacogenomic-guided drug therapy is at the forefront of personalized medicine with over 150 United States Food and Drug Administration (FDA) approved drug labels incorporating pharmacogenomic information.[1] Nonetheless, the translation of pharmacogenomic testing into routine clinical practice has been slow due to several obstacles towards its implementation [2][3][4]. Currently, the routine use of clinical pharmacogenomics is limited to centers with resources to overcome these obstacles [5][6][7][8][9].A major obstacle in the implementation of clinical pharmacogenomics is the rapid pace that science has identified genetic polymorphisms that can predict drug response. Th...

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“…1,13,15,16 To date however, clinical trials have not consistently demonstrated that dose prediction using warfarin algorithms improves anticoagulant control or patient outcomes compared to other methods. [17][18][19][20][21][22][23] For this reason, neither the American College of Chest Physicians (ACCP) 24 nor the British Committee for Standards in Haematology (BCSH) 25 consensus guideline advocate the use of dose prediction tools or genotyping prior to the initiation of therapy.…”

Section: Introductionmentioning

confidence: 99%

Influence of Genotype on Warfarin Maintenance Dose Predictions Produced Using a Bayesian Dose Individualization Tool

Saffian

Duffull

Roberts

et al. 2016

Therapeutic Drug Monitoring

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Randomized Trial of Genotype-Guided Versus Standard Warfarin Dosing in Patients Initiating Oral Anticoagulation

Cited by 630 publications

References 37 publications

Accuracy assessment of pharmacogenetic algorithms for warfarin dose prediction in Chinese patients

Accuracy assessment of pharmacogenetic algorithms for warfarin dose prediction in Chinese patients

Iterative Development and Evaluation of a Pharmacogenomic-Guided Clinical Decision Support System for Warfarin Dosing

Influence of Genotype on Warfarin Maintenance Dose Predictions Produced Using a Bayesian Dose Individualization Tool

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