Warfarin Dosing Algorithm Research Articles

Accuracy of an internationally validated genetic-guided warfarin dosing algorithm compared to a clinical algorithm in an Arab population

PurposeTo identify the impact of CYP2C9*2, *3, VKORC1−1639 G>A and CYP4F2*3 on warfarin dose in an Arab population. To compare the accuracy of a clinical warfarin dosing (CWD) versus genetic warfarin dosing algorithms (GWD) during warfarin initiation. MethodsA cohort of Arab patients newly starting on warfarin had their dose calculated using CWD published in www.warfarindosing.org and were followed for 1 month. Each patient provided a saliva sample. DNA was extracted, purified and genotyped for VKORC−1639 G>A, CYP2C9*2, CYP2C9*3 and CYP4F2*3. After reaching warfarin maintenance dose, the dose was recalculated using the GWD and median absolute error (MAE) and the percentage of warfarin doses within 20% of the actual dose were calculated and compared for the two algorithms. ResultsThe study enrolled 130 patients from 12 Arabian countries. Compared to those with wild type, carriers of reduced function alleles in CYP2C9 required significantly lower median (IQR) warfarin weekly dose [24.5 (15.3) vs. 35 (29.8) mg/week, p=0.006]. With regards to VKORC, patients with AA genotype had a significantly lower median (IQR) weekly warfarin dose compared to AG and GG [21(10.5) vs 29.4 (21), p<0.001 for AA vs AG, p<0.001 for AA vs GG]. The MAE (IQR) for the weekly dose of the GWD was significantly lower compared to CWD [8.1 (10.5) vs 12.4 (12.6) (p<0.001)]. ConclusionCYP2C9 and VKORC1 variants are important determinants of warfarin dose in the Arab population. The use of the genetic and clinical factors led to better warfarin dose estimation when compared to clinical factors alone.

Warfarin–A natural anticoagulant: A review of research trends for precision medication

BackgroundWarfarin is a widely prescribed anticoagulant in the clinic. It has a more considerable individual variability, and many factors affect its variability. Mathematical models can quantify the quantitative impact of these factors on individual variability. PurposeThe aim is to comprehensively analyze the advanced warfarin dosing algorithm based on pharmacometrics and machine learning models of personalized warfarin dosage. MethodsA bibliometric analysis of the literature retrieved from PubMed and Scopus was performed using VOSviewer. The relevant literature that reported the precise dosage of warfarin calculation was retrieved from the database. The multiple linear regression (MLR) algorithm was excluded because a recent systematic review that mainly reviewed this algorithm has been reported. The following terms of quantitative systems pharmacology, mechanistic model, physiologically based pharmacokinetic model, artificial intelligence, machine learning, pharmacokinetic, pharmacodynamic, pharmacokinetics, pharmacodynamics, and warfarin were added as MeSH Terms or appearing in Title/Abstract into query box of PubMed, then humans and English as filter were added to retrieve the literature. ResultsBibliometric analysis revealed important co-occuring MeShH and index keywords. Further, the United States, China, and the United Kingdom were among the top countries contributing in this domain. Some studies have established personalized warfarin dosage models using pharmacometrics and machine learning-based algorithms. There were 54 related studies, including 14 pharmacometric models, 31 artificial intelligence models, and 9 model evaluations. Each model has its advantages and disadvantages. The pharmacometric model contains biological or pharmacological mechanisms in structure. The process of pharmacometric model development is very time- and labor-intensive. Machine learning is a purely data-driven approach; its parameters are more mathematical and have less biological interpretation. However, it is faster, more efficient, and less time-consuming. Most published models of machine learning algorithms were established based on cross-sectional data sourced from the database. ConclusionFuture research on personalized warfarin medication should focus on combining the advantages of machine learning and pharmacometrics algorithms to establish a more robust warfarin dosage algorithm. Randomized controlled trials should be performed to evaluate the established algorithm of warfarin dosage. Moreover, a more user-friendly and accessible warfarin precision medicine platform should be developed.

Optimisation of warfarin-dosing algorithms for Han Chinese patients with CYP2C9*13 variants.

Existing pharmacogenetic algorithms cannot fully explain warfarin dose variability in allpatients. CYP2C9*13 is an important allelic variant in the Han Chinese population. However, adjustment of warfarin dosing in CYP2C9*13 variant carriers remains unclear. To the best of our knowledge, this study is the first to assess the effects of adjusting warfarin dosages in Han Chinese patients harbouring CYP2C9*13 variants. In total, 971 warfarin-treated Han Chinese patients with atrial fibrillation were enrolled in this study. Clinical data were collected, and CYP2C9*2, *3, *13 and VKORC1-1639 G > A variants were genotyped. We quantitatively analysed the effect of CYP2C9*13 on warfarin maintenance dose and provided multiplicative adjustments for CYP2C9*13 using validated pharmacogenetic algorithms. Approximately 0.6% of the Han Chinese population carried CYP2C9*13 variant, and the genotype frequency was between those of CYP2C9*2 and CYP2C9*3. The warfarin maintenance doses were significantly reduced in CYP2C9*13 carriers. When CYP2C9*13 variants were not considered, the pharmacogenetic algorithms overestimated warfarin maintenance doses by 1.03-1.16mg/d on average. The actual warfarin dose in CYP2C9*13 variant carriers was approximately 40% lower than the algorithm-predicted dose. Adjusting the warfarin-dosing algorithm according to the CYP2C9*13 allele could reduce the dose prediction error. Our study showed that the algorithm-predicted doses should be lowered for CYP2C9*13 carriers. Inclusion of the CYP2C9*13 variant in the warfarin-dosing algorithm tends to predict the warfarin maintenance dose more accurately and improves the efficacy and safety of warfarin administration in Han Chinese patients.

Evaluation of a warfarin dosing algorithm including CYP2C9, VKORC1, and CYP4F2 polymorphisms and non-genetic determinants for the Iranian population.

The response to warfarin, as an oral anticoagulant agent, varies widely among patients from different ethnic groups. In this study, we tried to ascertain and determine the relationship between non-genetic factors and genetic polymorphisms with warfarin therapy; we then proposed a new warfarin dosing prediction algorithm for the estimation of drug sensitivity and resistance in the Iranian population. Overall, 200 warfarin-treated patients with stable doses were recruited, the demographic and clinical characteristics were documented, and genotyping was done using a sequencing assay. The outcomes of our investigation showed that the genetic polymorphisms of VKORC1(-1639 G > A), CYP2C9*3, CYP2C9*2, amiodarone use, and increasing age were found to be related to a significantly lower mean daily warfarin dose. In contrast, the CYP4F2*3 variant and increased body surface area were linked with an increased dose of warfarin in the Iranians. Our descriptive model could describe 56.5% of the variability in response to warfarin. This population-specific dosing model performed slightly better than other previously published warfarin algorithms for our patient's series. Furthermore, our findings provided the suggestion that incorporating the CYP4F2*3 variant into the dosing algorithm could result in a more precise calculation of warfarin dose requirements in the Iranian population. We proposed and validated a population-specific dosing algorithm based on genetic and non-genetic determinants for Iranian patients and evaluated its performance. Accordingly, by using this newly developed algorithm, prescribers could make more informed decisions regarding the treatment of Iranian patients with warfarin.

Developing Chinese race-specific warfarin dose prediction algorithms.

Numerous genotype-guided warfarin dosing algorithms have been developed to individualize warfarin doses, but they can only explain 47-52% of the variability. This study aimed to develop new warfarin algorithms suitable to predict the stable warfarin dose for the Chinese population and to compare their prediction performance with those of the most commonly used algorithms. Multiple linear regression analysis with the warfarin optimal dose (WOD), logarithm (log) WOD, 1/WOD, and [Formula: see text], respectively, as the dependent variables were performed to deduce a new warfarin algorithm (NEW-Warfarin). WOD was the stable dose that maintained the international normalized ratio (INR) within the target range (2.0-3.0). Three major genotype-guided warfarin dosing algorithms were selected and compared against NEW-Warfarin predictive performance using the mean absolute error (MAE). Furthermore, patients were divided into five groups according to warfarin indications [atrial fibrillation (AF), pulmonary embolism (PE), cardiac-related disease (CRD), deep vein thrombosis (DVT), and other diseases (OD)]. Multiple linear regression analyses were also performed for each group. The regression equation with [Formula: see text] as the dependent variable had the highest coefficient of determination (R2 = 0.489). The NEW-Warfarin had the best predictive accuracy compared to the three algorithms selected. Group analysis, according to indications, showed that the R2 of the five groups were PE (0.902) > DVT (0.608) > CRD (0.569) > OD (0.436) > AF (0.424). Dosing algorithms based on warfarin indications are more suitable for predicting warfarin doses. Our research provides a novel strategy to develop indication-specific warfarin dosing algorithms to improve the efficacy and safety of warfarin prescribing.

Comparison of Maintenance Dose Predictions by Warfarin Dosing Algorithms Based on Chinese and Western Patients.

Warfarin has a long record of safe and effective clinical use, and it remains one of the most commonly prescribed drugs for the prevention and treatment of thromboembolic conditions even in the era of direct oral anticoagulants. To address its large interindividual variability and narrow therapeutic window, the Clinical Pharmacogenetics Implementation Consortium has recommended using pharmacogenetic dosing algorithms, such as the ones developed by the International Warfarin Pharmacogenetics Consortium (IWPC) and by Gage et al, to dose warfarin when genotype information is available. In China, dosing algorithms based on local patient populations have been developed and evaluated for predictive accuracy of warfarin maintenance doses. In this study, percentage deviations of doses predicted by 15 Chinese dosing algorithms from that by IWPC and Gage algorithms were systematically evaluated to understand the differences between Chinese and Western algorithms. In general, dose predictions by Chinese dosing algorithms tended to be lower than those predicted by IWPC or Gage algorithms for the most prevalent VKORC1 and CYP2C9 genotypes in the Chinese population. The extent of negative prediction deviation appeared to be largest in the younger age group with smaller body weight. Our findings are consistent with previous reports that Asians have a higher sensitivity to warfarin and require lower doses than Western populations.

Pharmacogenomics implementation in cardiovascular disease in a highly diverse population: initial findings and lessons learned from a pilot study in United Arab Emirates

BackgroundPharmacogenomic (PGx) testing has proved its utility and cost-effectiveness for some commonly prescribed cardiovascular disease (CVD) medications. In addition, PGx-guided dosing guidelines are now available for multiple CVD drugs, including clopidogrel, warfarin, and statins. The United Arab Emirates (UAE) population is diverse and multiethnic, with over 150 nationalities residing in the country. PGx-testing is not part of the standard of care in most global healthcare settings, including the UAE healthcare system. The first pharmacogenomic implementation clinical study in CVD has been approved recently, but multiple considerations needed evaluation before commencing. The current report appraises the PGx-clinical implementation procedure and the potential benefits of pursuing PGx-implementation initiatives in the UAE with global implications.MethodsPatients prescribed one or more of the following drugs: clopidogrel, atorvastatin, rosuvastatin, and warfarin, were recruited. Genotyping selected genetic variants at genes interacting with the study drugs was performed by real-time PCR.ResultsFor the current pilot study, 160 patients were recruited. The genotypes and inferred haplotypes, diplotypes, and predicted phenotypes revealed that 11.9% of the participants were poor CYP2C19 metabolizers, 35% intermediate metabolizers, 28.1% normal metabolizers, and 25% rapid or ultrarapid metabolizers. Notably, 46.9% of our cohort should receive a recommendation to avoid using clopidogrel or consider an alternative medication. Regarding warfarin, only 20% of the participants exhibited reference alleles at VKORC1-1639G > A, CYP2C9*2, and CYP2C9*3, leaving 80% with alternative genotypes at any of the two genes that can be integrated into the warfarin dosing algorithms and can be used whenever the patient receives a warfarin prescription. For statins, 31.5% of patients carried at least one allele at the genotyped SLCO1B1 variant (rs4149056), increasing their risk of developing myopathy. 96% of our cohort received at least one PGx-generated clinical recommendation for the studied drugs.ConclusionThe current pilot analysis verified the feasibility of PGx-testing and the unforeseen high frequencies of patients currently treated with suboptimal drug regimens, which may potentially benefit from PGx testing.

A genome-wide association study of plasma concentrations of warfarin enantiomers and metabolites in sub-Saharan black-African patients.

Diversity in pharmacogenomic studies is poor, especially in relation to the inclusion of black African patients. Lack of funding and difficulties in recruitment, together with the requirement for large sample sizes because of the extensive genetic diversity in Africa, are amongst the factors which have hampered pharmacogenomic studies in Africa. Warfarin is widely used in sub-Saharan Africa, but as in other populations, dosing is highly variable due to genetic and non-genetic factors. In order to identify genetic factors determining warfarin response variability, we have conducted a genome-wide association study (GWAS) of plasma concentrations of warfarin enantiomers/metabolites in sub-Saharan black-Africans. This overcomes the issue of non-adherence and may have greater sensitivity at genome-wide level, to identify pharmacokinetic gene variants than focusing on mean weekly dose, the usual end-point used in previous studies. Participants recruited at 12 outpatient sites in Uganda and South Africa on stable warfarin dose were genotyped using the Illumina Infinium H3Africa Consortium Array v2. Imputation was conducted using the 1,000 Genomes Project phase III reference panel. Warfarin/metabolite plasma concentrations were determined by high-performance liquid chromatography with tandem mass spectrometry. Multivariable linear regression was undertaken, with adjustment made for five non-genetic covariates and ten principal components of genetic ancestry. After quality control procedures, 548 participants and 17,268,054 SNPs were retained. CYP2C9*8, CYP2C9*9, CYP2C9*11, and the CYP2C cluster SNP rs12777823 passed the Bonferroni-adjusted replication significance threshold (p < 3.21E-04) for warfarin/metabolite ratios. In an exploratory GWAS analysis, 373 unique SNPs in 13 genes, including CYP2C9*8, passed the Bonferroni-adjusted genome-wide significance threshold (p < 3.846E-9), with 325 (87%, all located on chromosome 10) SNPs being associated with the S-warfarin/R-warfarin outcome (top SNP rs11188082, CYP2C19 intron variant, p = 1.55E-17). Approximately 69% of these SNPs were in linkage disequilibrium (r 2 > 0.8) with CYP2C9*8 (n = 216) and rs12777823 (n = 8). Using a pharmacokinetic approach, we have shown that variants other than CYP2C9*2 and CYP2C9*3 are more important in sub-Saharan black-Africans, mainly due to the allele frequencies. In exploratory work, we conducted the first warfarin pharmacokinetics-related GWAS in sub-Saharan Africans and identified novel SNPs that will require external replication and functional characterization before they can be considered for inclusion in warfarin dosing algorithms.

PHARMACOGENETIC TESTING AS AN ELEMENT OF PERSONALIZED MEDICINE IN REAL CLINICAL PRACTICE

Introduction . It has been proven that patients with thrombosis and with a high risk of systemic thromboembolic complications (TEС), including patients with non-valvular atrial fibrillation (AF) should receive effective and safe antithrombotic therapy [1–3]. A personalized approach to prolonged AVK therapy is associated with an improvement in hemostasiological markers of thrombinemia and clinical outcomes in patients with VTE and non-valvular AF [4–8]. Materials and methods . Prospective study was carried out on the basis of the anticoagulant clinic (AC) of the Department of hemostasis and atherothrombosis laboratory of the state budgetary health institution of the Arkhangelsk region “First city clinical hospital named after names E. E. Volosevich” (GBUZ AR FCCH). The object of the study is patients of the AVK registry who applied to the RCATT (n = 107) who underwent pharmacogenetic testing (CYP2C9, CYP4F2, VKORC1 genotype) with calculation of individual doses of warfarin and assessment of quality of life using validated questionnaires. The analysis of the effectiveness and safety of warfarin therapy was carried out. Results . It was found that complications of warfarin therapy developed regardless of the presence of the genotype (CYP2C9, CYP4F2, VKORC1) and the warfarin dosing algorithm under observation in AC. It has been shown that pharmacogenetic testing in patients with VTE and AF is an additional method under the condition of observation in AC. Conclusion . A personalized approach to prolonged VKA therapy using pharmacogenetic testing is appropriate for patients of the older age group, patients with a aggravated hemorrhagic history, frequent minor bleeding at target INR values and the presence of concomitant therapy with cytochrome P450 inhibitors.

Feasibility study of the Fearon Algorithm in anticoagulation service guided warfarin management

BackgroundPatients receiving warfarin who spend a lower proportion of time in therapeutic international normalized ratio (INR) range (TTR) have a higher risk of both bleeding complications and thromboembolic events. Using warfarin dosing algorithms is one intervention associated with improved INR stability. ObjectiveTo determine the feasibility of an individualized warfarin dosing algorithm (Fearon Algorithm) under anticoagulation management service (AMS) care and compare measures of INR control using the algorithm with standard care. MethodsA pre/post intervention feasibility study consisting of the 12 months prior to patient enrollment (pre-study phase) and 6 months in which patients used the Fearon Algorithm under the supervision of an AMS pharmacist (AMS phase). The primary study outcome was the change in individual TTR. ResultsA total of 30 patients were enrolled in the study, 26 (87%) of whom successfully completed the AMS study phase using the Fearon Algorithm. Median corrected individual TTR increased significantly from 53% (IQR: 39%, 64%) during the year prior to enrollment to 63% (IQR: 57%, 73%) during the AMS phase (p < 0.01) The uncorrected TTR also increased significantly from 52% (IQR: 39%, 64%) to 61% (IQR: 57%, 72%) (p < 0.01). The Fearon Algorithm specified a smaller warfarin tablet strength in half the patients. ConclusionThe Fearon Algorithm is feasible for an AMS to implement in patients receiving long-term warfarin therapy and appears to improve TTR.

Development of a system to support warfarin dose decisions using deep neural networks

The first aim of this study was to develop a prothrombin time international normalized ratio (PT INR) prediction model. The second aim was to develop a warfarin maintenance dose decision support system as a precise warfarin dosing platform. Data of 19,719 inpatients from three institutions was analyzed. The PT INR prediction algorithm included dense and recurrent neural networks, and was designed to predict the 5th-day PT INR from data of days 1–4. Data from patients in one hospital (n = 22,314) was used to train the algorithm which was tested with the datasets from the other two hospitals (n = 12,673). The performance of 5th-day PT INR prediction was compared with 2000 predictions made by 10 expert physicians. A generator of individualized warfarin dose-PT INR tables which simulated the repeated administration of varying doses of warfarin was developed based on the prediction model. The algorithm outperformed humans with accuracy terms of within ± 0.3 of the actual value (machine learning algorithm: 10,650/12,673 cases (84.0%), expert physicians: 1647/2000 cases (81.9%), P = 0.014). In the individualized warfarin dose-PT INR tables generated by the algorithm, the 8th-day PT INR predictions were within 0.3 of actual value in 450/842 cases (53.4%). An artificial intelligence-based warfarin dosing algorithm using a recurrent neural network outperformed expert physicians in predicting future PT INRs. An individualized warfarin dose-PT INR table generator which was constructed based on this algorithm was acceptable.

Warfarin dosing algorithms: A systematic review.

AimsNumerous algorithms have been developed to guide warfarin dosing and improve clinical outcomes. We reviewed the algorithms available for various populations and the covariates, performances and risk of bias of these algorithms.MethodsWe systematically searched MEDLINE up to 20 May 2020 and selected studies describing the development, external validation or clinical utility of a multivariable warfarin dosing algorithm. Two investigators conducted data extraction and quality assessment.ResultsOf 10 035 screened records, 266 articles were included in the review, describing the development of 433 dosing algorithms, 481 external validations and 52 clinical utility assessments. Most developed algorithms were for dose initiation (86%), developed by multiple linear regression (65%) and mostly applicable to Asians (49%) or Whites (43%). The most common demographic/clinical/environmental covariates were age (included in 401 algorithms), concomitant medications (270 algorithms) and weight (229 algorithms) while CYP2C9 (329 algorithms), VKORC1 (319 algorithms) and CYP4F2 (92 algorithms) variants were the most common genetic covariates. Only 26% and 7% algorithms were externally validated and evaluated for clinical utility, respectively, with <2% of algorithm developments and external validations being rated as having a low risk of bias.ConclusionMost warfarin dosing algorithms have been developed in Asians and Whites and may not be applicable to under‐served populations. Few algorithms have been externally validated, assessed for clinical utility, and/or have a low risk of bias which makes them unreliable for clinical use. Algorithm development and assessment should follow current methodological recommendations to improve reliability and applicability, and under‐represented populations should be prioritized.

Effects of rare CYP2C9 alleles on stable warfarin doses in Chinese Han patients with atrial fibrillation.

Aim: Gene polymorphisms are critical in warfarin dosing variation. Here, the role of rare CYP2C9 alleles on warfarin doses in Chinese Han patients was investigated. Methods: A retrospective study recruited 681 warfarin treated atrial fibrillation patients. The genetic and clinical data were collected. Dose-related variables were selected by univariate analyses and the warfarin-dosing algorithm was derived by multivariate regression analysis. Results: Three rare CYP2C9 alleles (CYP2C9*13, *16 and*60) were associated with lower stable doses. Inclusion of the rare CYP2C9 alleles in the prediction model added an extra 3.7% warfarin dose predictive power. Conclusion:CYP2C9*13, *16 and*60 was associated with lower stable warfarin doses in Chinese patients. The algorithm including rare CYP2C9 alleles tends to more accurately predict stable warfarin doses.

Quality of oral anticoagulation control in Chinese patients with non-valvular atrial fibrillation: a prospective controlled study

Objective The sex, age, medical history, treatment, tobacco use, race risk (SAMe-TT2R2) Score; the sex, age, medical history, treatment, tobacco use, genotype combination (SAMe-TT2G2) Score; and the so-called modified SAMe-TT2R2 scores have been proposed to predict the anticoagulation quality for patients with non-valvular atrial fibrillation (NVAF). The data from a prospective controlled study is used to validate the SAMe-TT2R2 and SAMe-TT2G2 scores in Chinese NVAF patients treated with warfarin and to evaluate the association of factors with time in therapeutic range (TTR) to predict the quality of oral anticoagulation control. Methods A total of 379 patients with NVAF under warfarin treatment for a three-month follow-up were included in this prospective, multicenter study. The quality of oral anticoagulation control was evaluated by the TTR. The TTR was dichotomized for binary logistic regression analysis, using a cutoff point for classification as an inadequate (TTR < 65.0%) control. Results The 379 NVAF patients had a mean TTR of 58.35 ± 26.33% and median SAMe-TT2R2 and SAMe-TT2G2 scores of 3 and 2, respectively. The discrimination performances of the SAMe-TT2R2 and SAMe-TT2G2 scores for inadequate anticoagulation control (TTR < 65.0%) were poor (c-index < 0.60). The gene frequency of CYP2C9*3 was 3.2% and that of VKORC1-1639 G > A was 89.3%. Genetic variation of CYP2C9*3 and VKORC1-1639 G > A did not affect TTR after initial treatment. The condition TTR < 65.0% was associated with an age below 60 without genotype-guided warfarin dose initiation and concomitant torasemide. Conclusions A warfarin-dosing algorithm used for initial treatment of patients older than 60 helps to achieve a better quality of oral anticoagulation control, whereas concomitant torasemide can produce a negative effect. These findings provide useful information for future investigations on the quality of oral anticoagulation control in Chinese anticoagulation clinical practice.

Pharmacogenetic-Guided Algorithm to Improve Daily Dose of Warfarin in Elder Han-Chinese Population.

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.

Verification of accuracy of warfarin stable dose prediction models in Shandong population

To compare the accuracy of five warfarin-dosing algorithms and warfarin stable dose model (2.5 mg/day) for Shandong population. One hundred and twenty five patients who achieved stable warfarin dose were enrolled. Clinical and genetic data were used to evaluate the value of each algorithm by calculating the percentage of patients whose predicted warfarin dose was within 20% of the actual stable therapeutic dose and mean absolute error (MAE). The frequency of patients with CYP2C9*1/*1, CYP2C9*1/*3 and CYP2C9*1/*2 genotype was 92.00%, 7.20%, 0.80%, respectively. That of VKORC1-1639 AA, AG and GG genotype was 82.40%, 15.20%, 2.40%, respectively. CYP4F2*1/*1, *1/*3, *3/*3 genotype was 50.40%, 39.20%, 10.40%, respectively. With the same genotypes for other loci, patients who carried at least one VKORC1-16398G mutant allele had increased warfarin stable daily dose compared with VKORC1-1639AA. Compared with CYP4F2*1/*1, those carrying at least one CYP4F2*3 mutant allele had warfarin stable daily dose increased by 5.9%-13.00%. The percentage of ideal prediction calculated from IWPC model (59.20%), Huang model (57.60%) and Ohno model (52.80%) were higher than others. The MAE were 0.35 (95%CI: 0.11-0.49), 0.15 (95%CI: 0.10-0.32), 0.39 (95%CI: 0.12-0.51), respectively. The polymorphisms of CYP2C9, VKORC1 and CYP4F2 genes can influence the stable dose of warfarin in Shandong population. IWPC algorithm is suitable for guiding the use of warfarin in this population.

Pharmacogenetic-guided and clinical warfarin dosing algorithm assessments with bleeding outcomes risk-stratified by genetic and covariate subgroups

BackgroundSafe administration of warfarin presents challenges due to a narrow therapeutic INR range and significant variability in inter-individual dose response. Bleeding secondary to warfarin use is a leading cause of hospitalization. MethodsFive warfarin dosing algorithms were assessed for accuracy of predicted compared to the INR target dose for patients with a HAS-BLED score ≥3 participating in the ENGAGE-AF TIMI 48 trial. Three warfarin metabolism subgroups (normal, sensitive, and highly sensitive responders) were established based on genotype. Mean differences between calculated and prescribed dose were determined for each algorithm across groups. ResultsA total of 7036 patients were analyzed and 1846 participants with HAS-BLED ≥3 were genotyped. The mean absolute error of predicted versus INR target dose for warfarin ranged from 8.1 mg/week on the pharmacogenetic-guided International Warfarin Pharmacogenetics Consortium (IWPC) and Gage algorithms to 11.3 mg/week on fixed dose. Overestimation of INR target dose occurred in 98% of highly sensitive responders by 21 mg/week for subjects on fixed dose. Pharmacogenetic-guided IWPC saw 89% overestimation with mean difference of 8.3 mg/week for highly sensitive responders. Major or clinically relevant non-major bleeding in the first 90 days of beginning warfarin was 3.27 times more likely for highly sensitive than normal responders. ConclusionsInitial doses were higher than INR target doses in high-risk bleeding subpopulations as defined by the modified HAS-BLED and genotype sensitivity analysis when compared to established algorithms. Clinical and pharmacogenetic-guided algorithms improved dosing in highly sensitive responders with HAS-BLED ≥3 compared to fixed dosing.

A cross-sectional evaluation of five warfarin anticoagulation services in Uganda and South Africa.

Warfarin is the most commonly prescribed oral anticoagulant in sub-Saharan Africa and requires ongoing monitoring. The burden of both infectious diseases and non-communicable diseases is high and medicines used to treat comorbidities may interact with warfarin. We describe service provision, patient characteristics, and anticoagulation control at selected anticoagulation clinics in Uganda and South Africa. We evaluated two outpatient anticoagulation services in Kampala, Uganda and three in Cape Town, South Africa between 1 January and 31 July 2018. We collected information from key staff members about the clinics' service provision and extracted demographic and clinical data from a sample of patients' clinic records. We calculated time in therapeutic range (TTR) over the most recent 3-month period using the Rosendaal interpolation method. We included three tertiary level, one secondary level and one primary level anticoagulation service, seeing between 30 and 800 patients per month. Care was rendered by nurses, medical officers, and specialists. All healthcare facilities had on-site pharmacies; laboratory INR testing was off-site at two. Three clinics used warfarin dose-adjustment protocols; these were not validated for local use. We reviewed 229 patient clinical records. Most common indications for warfarin were venous thrombo-embolism in 112/229 (49%), atrial fibrillation in 74/229 (32%) and valvular heart disease in 30/229 (13%). Patients were generally followed up monthly. HIV prevalence was 20% and 5% at Ugandan and South African clinics respectively. Cardiovascular comorbidity predominated. Furosemide, paracetamol, enalapril, simvastatin, and tramadol were the most common concomitant drugs. Anticoagulation control was poor at all included clinics with median TTR of 41% (interquartile range 14% to 69%). TTR was suboptimal at all included sites, despite frequent patient follow-up. Strategies to improve INR control in sub-Saharan patients taking warfarin are needed. Locally validated warfarin dosing algorithms in Uganda and South Africa may improve INR control.

The Contribution of VKORC1 and CYP2C9 Genetic Polymorphisms and Patients' Demographic Characteristics with Warfarin Maintenance Doses: A Suggested Warfarin Dosing Algorithm.

The requirement of varying doses of warfarin for different individuals can be explained by environmental and genetic factors. We evaluated the frequency of vitamin K epoxide reductase complex subunit 1 (VKORC1) and cytochrome P450 2C9 (CYP2C9) variants together with patientdemographic characteristics and investigated their association with warfarin dose requirement with the objective to suggest a warfarin dosing algorithm. In this study, 185 patients with heart valve replacement from West Azerbaijan, Iran were genotyped for VKORC1 (-1639 G>A) and CYP2C9 (*2 and *3 alleles) by PCR-RFLP. Multiple linear regression was performed to create a new warfarin dosing algorithm. The frequency of variants in studied subjects was 12% for CYP2C9 *2, 25.8% for CYP2C9 *3, and 60% for -1639A. The patients who carried the A allele at position -1639 VKORC1 and the variants CYP2C9 *2 and *3 required a significantly lower daily mean warfarin dosage (P = 0.001). Statistical analysis also indicated a significant relationship between the daily maintenance dose of warfarin with age and blood pressure among the studied patients’ cohort (P < 0.001). This study showed that in the heart valve replacement patients considering VKORC1 and CYP2C9 polymorphisms beside demographic characteristics such as age will be helpful in pre-treatment dosing of warfarin which in turn reduces the complications associated with inappropriate warfarin dosing.

Development and Validation of a Novel Warfarin Dosing Algorithm for Korean Patients With VKORC1 1173C.

BackgroundDifferences in the performance of suggested warfarin dosing algorithms among different ethnicities and genotypes have been reported; this necessitates the development of an algorithm with enhanced performance for specific population groups. Previous warfarin dosing algorithms underestimated warfarin doses in VKORC1 1173C carriers. We aimed to develop and validate a new warfarin dosing algorithm for Korean patients with VKORC1 1173C.MethodsA total of 109 patients carrying VKORC1 1173CT (N=105) or 1173CC (N=4) were included in this study. Multiple regression analysis was performed to deduce a new dosing algorithm. Following literature searches for genotype-guided warfarin dosing algorithms, 21 algorithms were selected and evaluated using the correlation coefficient (ρ) of actual dose and estimated dose, mean error, and root mean square error.ResultsThe developed algorithm is as follows: maintenance dose (mg/week)=exp [3.223−0.009×(age)+0.577×(body surface area [BSA])+0.178×(sex)−0.481×(CYP2C9 genotype)+0.227×(VKORC1 genotype)]. Integrated variables explained 44% of the variance in the maintenance dose. The predicted and actual doses showed moderate correlation (ρ=0.641) with the best performance with a mean error of −1.30 mg/week. The proportion of underestimated groups was 17%, which was lower than with the other algorithms.ConclusionsThis is the first study to develop and validate a warfarin dosing algorithm based on data from VKORC1 1173C carriers; it showed superior predictive performance compared with previously published algorithms.