Population pharmacokinetics of racemic warfarin in adult patients

Mungall, Dennis; Ludden, Thomas M.; Marshall, James D.; Hawkins, David; Talbert, Robert L.; Crawford, Michael H.

doi:10.1007/bf01065653

Cited by 91 publications

(51 citation statements)

References 21 publications

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“…The effect of smoking (ϩ 20.1%) was larger than expected, since hepatic enzyme induction from smoking results in only a 10% increase in warfarin clearance. 29 Directionally, however, this is consistent with other For personal use only. on May 9, 2018. by guest www.bloodjournal.org From studies that have shown a significant relationship between smoking status and warfarin dose.…”

Section: Discussionsupporting

confidence: 85%

Genetic-based dosing in orthopedic patients beginning warfarin therapy

Millican

Lenzini

Milligan

et al. 2007

Blood

159

139

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IntroductionWarfarin sodium is characterized by a narrow therapeutic range (eg, an international normalized ratio [INR]) of 2.0-3.0), a marked interindividual variation in dosing requirements, and an increased risk of adverse events when the dose is too high or low. 1,2 To minimize the high incidence of such events, [3][4][5] particularly during the first few weeks of initiating therapy, 1,6 most guidelines recommend prescribing warfarin at or near the anticipated maintenance dose and then adjusting the dose by trial and error. 1,7,8 While algorithms for predicting this maintenance dose a priori have improved, [9][10][11][12][13][14][15][16] there remains little guidance on how this starting dose should be adjusted a posteriori based on the subsequent INR values. We hypothesized that use of genetic markers could help optimize these dose refinements.Two common single nucleotide polymorphisms (SNPs) in the cytochrome P450 (CYP) 2C9 system are associated with impaired metabolism of warfarin, [3][4][5][6]11,17 while SNPs in the gene for vitamin K epoxide reductase complex 1 (VKORC1) correlate with warfarin sensitivity and resistance. 2,[18][19][20] No prior study has examined the impact of these SNPs on warfarin-dose adjustments. Given the current knowledge about these markers, we hypothesize that for a given INR, a patient who is a slow metabolizer of warfarin may need a more cautious adjustment in their dose than a similar patient who is a normal metabolizer. Failure to tailor dose refinements during warfarin induction in poor metabolizers may have contributed to the 3-fold increased risk of (laboratory or clinical) adverse events among poor metabolizers in our initial prospective study of pharmacogenetic-based warfarin therapy. 4 The purpose of this study was to develop a dose-refinement nomogram to guide clinicians in adjusting warfarin doses. This nomogram would be similar to prior algorithms, 21,22 but will have 2 advantages: (1) it will allow for, but not require, a first dose that is tailored to clinical and/or genetic factors and (2) it will incorporate genetics and clinical factors that are independent predictors of how much the dose should be refined. 1,11 If successful, the proposed warfarin nomogram would simplify and standardize warfarin initiation. Patients, materials, and methodsThe study was a retrospective analysis of 2 cohorts of orthopedic surgery patients who had participated in 2 prospective studies of pharmacogeneticbased warfarin therapy. The Human Research Protection Office at Washington University Medical Center approved these studies. PatientsFor patients in both cohorts, we offered participation if they were scheduled for primary or revision total knee or hip arthroplasty at Washington University Medical Center and if they were 18 years or older. We excluded patients who had previously taken warfarin or who had contraindications to warfarin treatment. To allow time for genotyping, we also excluded patients scheduled for surgery fewer than 7 days following referral to our anticoagulation s...

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Section: Discussionsupporting

confidence: 85%

Genetic-based dosing in orthopedic patients beginning warfarin therapy

Millican

Lenzini

Milligan

et al. 2007

Blood

159

139

View full text Add to dashboard Cite

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“…18 In keeping with the need for ease of use in clinical practice, a simplified algorithm with only a few variables can be very intuitive in application and easily implemented, which is particularly appealing to busy physicians practicing in community settings. In addition, a simple genotypebased algorithm may be used in conjunction with the traditional dose adjustment for patients on amiodarone, namely an additional 15% to 22% dose reduction, given its known correlation with therapeutic dose 20,31,32 ; or with a 10% dose escalation for smokers. 20 Until prospective studies provide solid evidence for the advantage of using a complicated dosing algorithm, simple guidance in dose adjustment based on genotyping information can be helpful options to physicians.…”

Section: Clinical Applicationmentioning

confidence: 99%

Validation and Comparison of Pharmacogenetics-Based Warfarin Dosing Algorithms for Application of Pharmacogenetic Testing

Roper

Storer

Bona

et al. 2010

The Journal of Molecular Diagnostics

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Warfarin is a widely prescribed drug that is difficult to use because of its narrow therapeutic window. Genetic polymorphisms associated with warfarin metabolism have been identified , but the clinical utility of genetic testing in warfarin dosing has not been established. External validation of published algorithms is critical to determine the best prediction for warfarin dosing in prospective trials. We used two independent datasets totaling 1095 patients to evaluate four published algorithms and a simple prediction algorithm developed in this study based on the CYP2C9*2 , CYP2C9*3, and VKORC1 ؊1639 polymorphisms in 150 patients taking warfarin. Predicted warfarin doses were calculated and compared for accuracy with actual maintenance doses. All evaluated pharmacogenetics-based dosing algorithms performed similarly for both datasets. The proportion of variation explained (R 2 ) was high (60% to 65%) in the small white-only Connecticut dataset but low (36% to 46%) in the large dataset on a diverse ethnic population from the International Warfarin Pharmacogenetics Consortium (IWPC). When comparing the percentage of patients whose predicted dosage are within 20% of actual , the IWPC algorithm performed the best overall (45.9%) for the two datasets combined while other algorithms performed nearly as well. Because no algorithm could be considered the best for all dosing ranges , it may be important to consider the nature of a local service population in choosing the most appropriate pharmacogenetics-based dosing algorithm. Pharmacogenetics is a new and rapidly evolving discipline that addresses how genetic polymorphisms affect an individual's response to pharmacological agents. Also known as "personalized" medicine, pharmacogenetic testing is still not routinely used in clinical practice. One important direction in pharmacogenetics, warfarin therapy, has gained significant attention.Warfarin, a widely prescribed medication used by millions of Americans, is used to prevent venous and arterial thrombosis for patients with a variety of conditions. Unfortunately, the appropriate dose required is highly variable (up to 20-fold)-such that routine dosing can lead to major and fatal bleeding episodes.1-3 Current clinical warfarin guidelines are able to predict only 25% of variability in dosage. 3 In recent years, however, dosing algorithms incorporating common polymorphisms in a gene encoding a liver enzyme that metabolizes warfarin, cytochrome P 450 2C9 (CYP2C9), and in the gene for vitamin K epoxide reductase complex 1 (VKORC1) along with certain clinical characteristics (such as age, gender, and height) have been shown to predict approximately half of the interpatient variability in dosage. 4 -6 These studies led the U.S. Food and Drug Administration (FDA), in August 2007, to update the warfarin drug label to include information on how genetic polymorphisms can affect dosing (http://www.fda.gov/NewsEvents/ Newsroom/PressAnnouncements/2007/ucm108967.htm, last accessed August 5, 2009). Nonetheless, the American College...

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“…Such PK models address the underlying process of absorption, distribution, and elimination as model parameters, allowing for a better prediction. Population PK analyses resolve the observed variability into its interpatient and random assay within patient error components, but whereas these methods [13] have a long history of usage for the more common blood-clotting drugs, that is not the case with haemophilia treatments. Only recently a population analysis has been reported for factor VIII dose individualisation in healthy adults with haemophilia A before surgery [12,14].…”

Section: Introductionmentioning

confidence: 99%

Population pharmacokinetics of recombinant factor VIII:C (ReFacto®) in adult HIV-negative and HIV-positive haemophilia patients

Karafoulidou¹,

Súárez

Anastasopoulou³

et al. 2009

Eur J Clin Pharmacol

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Purpose The aim of this study was to explore possible differences in the pharmacokinetics (PK) of recombinant factor VIII:C (ReFacto® -ReFacto ) in HIV+ vs. HIVpatients and also differences in the chromogenic substrate bioassay (CHS) and one-stage clotting (OSC) methods. Methods Twenty-eight haemophilia A adults (20 HIV-and eight HIV+) were assayed with both the CHS and OSC methods. An average of two and six samples were collected per patient for HIV-/+, respectively, after one, and occasionally two more, prophylactic doses (mean 2,003 IU; range 1,000-4,300 IU). The observations were analysed with the mixed-effects (population) compartmental PK modelling package NONMEM (nonlinear mixed-effects modelling) and the FOCE (first-order conditional estimation) method. Base modelling was performed independently for the CHS and OSC bioassays for comparison, and covariate models and simulation tests were done only for the commonly used OSC bioassay. The final covariate model was validated using the bootstrap method. Monte Carlo simulations were used to estimate the expected probability of exceeding 20%, 40% or 60% of normal factor VIII:C in plasma after a single dose, corresponding to required levels for preventing mild, moderate and lifethreatening haemorrhages. Results One-compartment base-model population PK parameters were [mean parameter (interpatient variability %)] for CHS: clearance (CL)=2.56 dl h −1 (33.2%); volume of distribution (V)=34.8 dl (12.8%); and for OSC: CL= 3.83 dl h −1 (47.8%), V=53.7 dl (22.4%). The volumes differed significantly between the CHS and OSC methods (p<0.0001), and variabilities were higher for OSC. Nevertheless, the empirical half-lives (t 1/2 =l n (2) × V/CL) were similar for CHS and OSC, [(mean ± standard deviation (SD)], 9.5 ± 3 h and 10.2 ± 4 h, respectively. In covariate modelling with the OSC-derived model, HIV status (VIR) was a significant categorical predictor (p<0.005) for V.The final covariate models with OSC were for CL=3.93 + 0.09 × (WT-75) and for V=48.6 × (1 + 0.36 × VIR) + 0.55 × (WT-75); therefore, V for the typical HIV+ patient was 36% higher than for the HIV-patient. Conclusions Both HIV-and HIV+ patients showed 100% success with the 20% threshold at doses >20 IU/kg. HIVpatients receiving >50 IU/kg had a 100% expected chance of success for all thresholds. HIV+ patients for moderate or life-threatening haemorrhage treatment need 10 IU/kg more than the HIV-patient equivalent to have the same probability of success.

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Population pharmacokinetics of racemic warfarin in adult patients

Cited by 91 publications

References 21 publications

Genetic-based dosing in orthopedic patients beginning warfarin therapy

Genetic-based dosing in orthopedic patients beginning warfarin therapy

Validation and Comparison of Pharmacogenetics-Based Warfarin Dosing Algorithms for Application of Pharmacogenetic Testing

Population pharmacokinetics of recombinant factor VIII:C (ReFacto®) in adult HIV-negative and HIV-positive haemophilia patients

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