Use of pharmacogenetic and clinical factors to predict the therapeutic dose of warfarin.
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ABSTRACT:
SUBMITTER: Gage BF
PROVIDER: S-EPMC2683977 | biostudies-literature | 2008 Sep
REPOSITORIES: biostudies-literature
Publications
Use of pharmacogenetic and clinical factors to predict the therapeutic dose of warfarin.
Gage B F BF Eby C C Johnson J A JA Deych E E Rieder M J MJ Ridker P M PM Milligan P E PE Grice G G Lenzini P P Rettie A E AE Aquilante C L CL Grosso L L Marsh S S Langaee T T Farnett L E LE Voora D D Veenstra D L DL Glynn R J RJ Barrett A A McLeod H L HL
Clinical pharmacology and therapeutics 20080227 3
Initiation of warfarin therapy using trial-and-error dosing is problematic. Our goal was to develop and validate a pharmacogenetic algorithm. In the derivation cohort of 1,015 participants, the independent predictors of therapeutic dose were: VKORC1 polymorphism -1639/3673 G>A (-28% per allele), body surface area (BSA) (+11% per 0.25 m(2)), CYP2C9(*)3 (-33% per allele), CYP2C9(*)2 (-19% per allele), age (-7% per decade), target international normalized ratio (INR) (+11% per 0.5 unit increase), a ...[more]
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Project description:BACKGROUND:Genetic variability among patients plays an important role in determining the dose of warfarin that should be used when oral anticoagulation is initiated, but practical methods of using genetic information have not been evaluated in a diverse and large population. We developed and used an algorithm for estimating the appropriate warfarin dose that is based on both clinical and genetic data from a broad population base. METHODS:Clinical and genetic data from 4043 patients were used to create a dose algorithm that was based on clinical variables only and an algorithm in which genetic information was added to the clinical variables. In a validation cohort of 1009 subjects, we evaluated the potential clinical value of each algorithm by calculating the percentage of patients whose predicted dose of warfarin was within 20% of the actual stable therapeutic dose; we also evaluated other clinically relevant indicators. RESULTS:In the validation cohort, the pharmacogenetic algorithm accurately identified larger proportions of patients who required 21 mg of warfarin or less per week and of those who required 49 mg or more per week to achieve the target international normalized ratio than did the clinical algorithm (49.4% vs. 33.3%, P<0.001, among patients requiring < or = 21 mg per week; and 24.8% vs. 7.2%, P<0.001, among those requiring > or = 49 mg per week). CONCLUSIONS:The use of a pharmacogenetic algorithm for estimating the appropriate initial dose of warfarin produces recommendations that are significantly closer to the required stable therapeutic dose than those derived from a clinical algorithm or a fixed-dose approach. The greatest benefits were observed in the 46.2% of the population that required 21 mg or less of warfarin per week or 49 mg or more per week for therapeutic anticoagulation.
| S-EPMC2722908 | biostudies-literature
Project description:By guiding initial warfarin dose, pharmacogenetic (PGx) algorithms may improve the safety of warfarin initiation. However, once international normalised ratio (INR) response is known, the contribution of PGx to dose refinements is uncertain. This study sought to develop and validate clinical and PGx dosing algorithms for warfarin dose refinement on days 6-11 after therapy initiation. An international sample of 2,022 patients at 13 medical centres on three continents provided clinical, INR, and genetic data at treatment days 6-11 to predict therapeutic warfarin dose. Independent derivation and retrospective validation samples were composed by randomly dividing the population (80%/20%). Prior warfarin doses were weighted by their expected effect on S-warfarin concentrations using an exponential-decay pharmacokinetic model. The INR divided by that "effective" dose constituted a treatment response index . Treatment response index, age, amiodarone, body surface area, warfarin indication, and target INR were associated with dose in the derivation sample. A clinical algorithm based on these factors was remarkably accurate: in the retrospective validation cohort its R(2) was 61.2% and median absolute error (MAE) was 5.0 mg/week. Accuracy and safety was confirmed in a prospective cohort (N=43). CYP2C9 variants and VKORC1-1639 G?A were significant dose predictors in both the derivation and validation samples. In the retrospective validation cohort, the PGx algorithm had: R(2)= 69.1% (p<0.05 vs. clinical algorithm), MAE= 4.7 mg/week. In conclusion, a pharmacogenetic warfarin dose-refinement algorithm based on clinical, INR, and genetic factors can explain at least 69.1% of therapeutic warfarin dose variability after about one week of therapy.
| S-EPMC3292349 | biostudies-literature
Project description:Purpose of reviewTo review the most promising genetic markers associated with the variability in the safety or efficacy of warfarin and clopidogrel and highlight the verification and validation initiatives for translating clopidogrel and warfarin pharmacogenetic tests to clinical practice.Recent findingsRapid advances in pharmacogenetics, continuous decrease in genotyping cost, development of point-of-care devices and the newly established clinical genotyping programs at several institutions hold the promise of individualizing clopidogrel and warfarin based on genotype. Guidelines have been established to assist clinicians in prescribing clopidogrel or warfarin dose based on genotype. However, the clinical utility of clopidogrel and warfarin is still limited. Accordingly, large randomized clinical trials are underway to define the role of clopidogrel and warfarin pharmacogenetics in clinical practice.SummaryPharmacogenetics has offered compelling evidence toward the individualization of clopidogrel and warfarin therapies. The rapid advances in technology make the clinical implementation of clopidogrel and warfarin pharmacogenetics possible. The clinical genotyping programs and the ongoing clinical trials will help in overcoming some of the barriers facing the clinical implementation of clopidogrel and warfarin pharmacogenetics.
| S-EPMC3731766 | biostudies-literature
Project description:Pharmacogenetic dosing algorithms help predict warfarin maintenance doses, but their predictive performance differs in different populations, possibly due to unsuspected population-specific genetic variants. The objectives of this study were to quantify the effect of the VKORC1 D36Y variant (a marker of warfarin resistance previously described in 4% of Ashkenazi Jews) on warfarin maintenance doses and to examine how this variant affects the performance of the International Warfarin Pharmacogenetic Consortium (IWPC) dose prediction model. In 210 Israeli patients on chronic warfarin therapy recruited at a tertiary care centre, we applied the IWPC model and then added D36Y genotype as covariate to the model (IWPC+D36Y) and compared predicted with actual doses. Median weekly warfarin dose was 35 mg (interquartile range [IQR], 24.5 to 52.5 mg). Among 16 heterozygous D36Y carriers (minor allele frequency = 3.8%), warfarin weekly dose was increased by a median of 43.7 mg (IQR, 40.5 to 47.2 mg) compared to non-carriers after adjustment for all IWPC parameters, a greater than two-fold dose increase. The IWPC model performed suboptimally (coefficient of determination R²=27.0%; mean absolute error (MAE), 14.4 ± 16.2 mg/week). Accounting for D36Y genotype using the IWPC+D36Y model resulted in a significantly better model performance (R²=47.2%, MAE=12.6 ± 12.4 mg/week). In conclusion, even at low frequencies, variants with a strong impact on warfarin dose may greatly decrease the performance of a commonly used dose prediction model. Unexpected discrepancies of the performance of universal prediction models in subpopulations should prompt searching for unsuspected confounders, including rare genetic variants.
| S-EPMC3461592 | biostudies-literature
Project description:BackgroundThe clinical utility of genotype-guided (pharmacogenetically based) dosing of warfarin has been tested only in small clinical trials or observational studies, with equivocal results.MethodsWe randomly assigned 1015 patients to receive doses of warfarin during the first 5 days of therapy that were determined according to a dosing algorithm that included both clinical variables and genotype data or to one that included clinical variables only. All patients and clinicians were unaware of the dose of warfarin during the first 4 weeks of therapy. The primary outcome was the percentage of time that the international normalized ratio (INR) was in the therapeutic range from day 4 or 5 through day 28 of therapy.ResultsAt 4 weeks, the mean percentage of time in the therapeutic range was 45.2% in the genotype-guided group and 45.4% in the clinically guided group (adjusted mean difference, [genotype-guided group minus clinically guided group], -0.2; 95% confidence interval, -3.4 to 3.1; P=0.91). There also was no significant between-group difference among patients with a predicted dose difference between the two algorithms of 1 mg per day or more. There was, however, a significant interaction between dosing strategy and race (P=0.003). Among black patients, the mean percentage of time in the therapeutic range was less in the genotype-guided group than in the clinically guided group. The rates of the combined outcome of any INR of 4 or more, major bleeding, or thromboembolism did not differ significantly according to dosing strategy.ConclusionsGenotype-guided dosing of warfarin did not improve anticoagulation control during the first 4 weeks of therapy. (Funded by the National Heart, Lung, and Blood Institute and others; COAG ClinicalTrials.gov number, NCT00839657.).
| S-EPMC3942158 | biostudies-literature
Project description:CYP2C9 and VKORC1 genotypes predict therapeutic warfarin dose at initiation of therapy; however, the predictive ability of genetic information after a week or longer is unknown. Experts have hypothesized that genotype becomes irrelevant once international normalized ratio (INR) values are available because INR response reflects warfarin sensitivity.We genotyped the participants in the Prevention of Recurrent Venous Thromboembolism (PREVENT) trial, who had idiopathic venous thromboemboli and began low-intensity warfarin (therapeutic INR 1.5-2.0) using a standard dosing protocol. To develop pharmacogenetic models, we quantified the effect of genotypes, clinical factors, previous doses and INR on therapeutic warfarin dose in the 223 PREVENT participants who were randomized to warfarin and achieved stable therapeutic INRs.A pharmacogenetic model using data from day 0 (before therapy initiation) explained 54% of the variability in therapeutic dose (R(2)). The R(2) increased to 68% at day 7, 75% at day 14, and 77% at day 21, because of increasing contributions from prior doses and INR response. Although CYP2C9 and VKORC1 genotypes were significant independent predictors of therapeutic dose at each weekly interval, the magnitude of their predictive ability diminished over time: partial R(2) of genotype was 43% at day 0, 12% at day 7, 4% at day 14, and 1% at day 21.Over the first weeks of warfarin therapy, INR and prior dose become increasingly predictive of therapeutic dose, and genotype becomes less relevant. However, at day 7, genotype remains clinically relevant, accounting for 12% of therapeutic dose variability.
| S-EPMC3718044 | biostudies-literature
Project description:Despite some previous examples of successful application to the field of pharmacogenomics, the utility of machine learning (ML) techniques for warfarin dose predictions in Caribbean Hispanic patients has yet to be fully evaluated. This study compares seven ML methods to predict warfarin dosing in Caribbean Hispanics. This is a secondary analysis of genetic and non-genetic clinical data from 190 cardiovascular Hispanic patients. Seven ML algorithms were applied to the data. Data was divided into 80 and 20% to be used as training and test sets. ML algorithms were trained with the training set to obtain the models. Model performance was determined by computing the corresponding mean absolute error (MAE) and % patients whose predicted optimal dose were within ±20% of the actual stabilization dose, and then compared between groups of patients with "normal" (i.e., > 21 but <49 mg/week), low (i.e., ≤21 mg/week, "sensitive"), and high (i.e., ≥49 mg/week, "resistant") dose requirements. Random forest regression (RFR) significantly outperform all other methods, with a MAE of 4.73 mg/week and 80.56% of cases within ±20% of the actual stabilization dose. Among those with "normal" dose requirements, RFR performance is also better than the rest of models (MAE = 2.91 mg/week). In the "sensitive" group, support vector regression (SVR) shows superiority over the others with lower MAE of 4.79 mg/week. Finally, multivariate adaptive splines (MARS) shows the best performance in the resistant group (MAE = 7.22 mg/week) and 66.7% of predictions within ±20%. Models generated by using RFR, MARS, and SVR algorithms showed significantly better predictions of weekly warfarin dosing in the studied cohorts than other algorithms. Better performance of the ML models for patients with "normal," "sensitive," and "resistant" to warfarin were obtained when compared to other populations and previous statistical models.
| S-EPMC6987072 | biostudies-literature
Project description:Recent clinical trial data cast doubt on the utility of genotype-guided warfarin dosing, specifically showing worse dosing with a pharmacogenetic versus clinical dosing algorithm in African Americans. However, many genotypes important in African Americans were not accounted for. We aimed to determine whether omission of the CYP2C9*5, CYP2C9*6, CYP2C9*8, CYP2C9*11 alleles and rs12777823 G > A genotype affects performance of dosing algorithms in African Americans.In a cohort of 274 warfarin-treated African Americans, we examined the association between the CYP2C9*5, CYP2C9*6, CYP2C9*8, CYP2C9*11 alleles and rs12777823 G > A genotype and warfarin dose prediction error with pharmacogenetic algorithms used in clinical trials.The http://www.warfarindosing.org algorithm overestimated doses by a median (interquartile range) of 1.2 (0.02-2.6) mg/day in rs12777823 heterozygotes (P<0.001 for predicted vs. observed dose), 2.0 (0.6-2.8) mg/day in rs12777823 variant homozygotes (P = 0.004), and 2.2 (0.5-2.9) mg/day in carriers of a CYP2C9 variant (P < 0.001). The International Warfarin Pharmacogenetics Consortium (IWPC) algorithm underdosed warfarin by 0.8 (-2.3 to 0.4) mg/day for patients with the rs12777823 GG genotype (P < 0.001) and overdosed warfarin by 0.7 (-0.4 to 1.9) mg/day in carriers of a variant CYP2C9 allele (P = 0.04). Modifying the http://www.warfarindosing.org algorithm to adjust for variants important in African Americans led to better dose prediction than either the original http://www.warfarindosing.org (P < 0.01) or IWPC (P < 0.01) algorithm.These data suggest that, when providing genotype-guided warfarin dosing, failure to account for variants important in African Americans leads to significant dosing error in this population.
| S-EPMC4280295 | biostudies-literature
Project description:PurposeNumerous studies have investigated causes of warfarin dose variability in adults, whereas studies in children are limited both in numbers and size. Mechanism-based population modelling provides an opportunity to condense and propagate prior knowledge from one population to another. The main objectives with this study were to evaluate the predictive performance of a theoretically bridged adult warfarin model in children, and to compare accuracy in dose prediction relative to published warfarin algorithms for children.MethodAn adult population pharmacokinetic/pharmacodynamic (PK/PD) model for warfarin, with CYP2C9 and VKORC1 genotype, age and target international normalized ratio (INR) as dose predictors, was bridged to children using allometric scaling methods. Its predictive properties were evaluated in an external data set of children 0-18 years old, including comparison of dose prediction accuracy with three pharmacogenetics-based algorithms for children.ResultsOverall, the bridged model predicted INR response well in 64 warfarin-treated Swedish children (median age 4.3 years), but with a tendency to overpredict INR in children ≤2 years old. The bridged model predicted 20 of 49 children (41 %) within ± 20 % of actual maintenance dose (median age 7.2 years). In comparison, the published dosing algorithms predicted 33-41 % of the children within ±20 % of actual dose. Dose optimization with the bridged model based on up to three individual INR observations increased the proportion within ±20 % of actual dose to 70 %.ConclusionA mechanism-based population model developed on adult data provides a promising first step towards more individualized warfarin therapy in children.
| S-EPMC3651819 | biostudies-literature
Project description:ObjectivesTo verify the accuracy of the International Warfarin Pharmacogenetics Consortium (IWPC) algorithm, identify the effects of genetic and clinical factors on warfarin stable dose, and to establish a new warfarin stable dose prediction algorithm for the elderly Han-Chinese population under the guidance of pharmacogenetics.MethodsAccording to the inclusion criteria, 544 non-valvular atrial fibrillation patients taking warfarin for anticoagulation treatment were enrolled. Data information of three groups including the whole population, people under 65 years old and over 65 years old were substituted into the IWPC algorithm respectively to verify its accuracy. The basic data and clinical information of 360 elderly people were collected for statistical analysis and the genotypes of VKORC1-G1639A and CYP2C9 were detected by Sanger sequencing. The new algorithm of the elder pharmacogenetics warfarin dosing was obtained by stepwise multiple regression. The determination coefficient (R2), root mean squared error (RMSE), and the proportion of the predicted value within the true value range of ±20%(20%-p) were used to evaluate the accuracy of the IWPC algorithm and the new algorithm.ResultsAmong the three different age groups, the warfarin stable dose predictive accuracy of IWPC algorithm was the lowest in the elderly patients above 65-year-old. In this study, the important factors influencing the stable dose of warfarin in the elderly Han-Chinese were height, weight, body surface area, serum creatinine level, amiodarone usage, CYP2C9 (*1*2, *1*3), and VKORC1 (GG/GA) genotypes. By means of stepwise multiple regression analysis, we established a new elder warfarin dosing algorithm (R2=0.3714) containing height, creatinine, amiodarone usage, CYP2C9 (*1*2 or *1*3), and VKORC1 (GA or GG) genotypes. The prediction accuracy and clinical availability of the Elderly algorithm was significantly better than that of IWPC algorithm verified by RMSE, R2, and (20%-p) methods.ConclusionsThe IWPC model may not be suitable for the elder Han-Chinese population. Polymorphism of CYP2C9 and VKORC1 obviously affected warfarin stable dose of the elder Han-Chinese. Combination of genetic data with demographic and clinical factors could help to better improve warfarin doses in the elder Han-Chinese population.
| S-EPMC7365937 | biostudies-literature