Estimation of the warfarin dose with a pharmacogenetic refinement algorithm in Chinese patients mainly under low-intensity warfarin anticoagulation

2012 ◽  
Vol 108 (12) ◽  
pp. 1132-1140 ◽  
Author(s):  
Jie Yang ◽  
Lei Gao ◽  
Yan Zhang ◽  
Hongjuan Wang ◽  
Caiyi Lu ◽  
...  
Keyword(s):  
Validation Cohort ◽  
Warfarin Dose ◽  
Chinese Patients ◽  
Fixed Dose ◽  
Dose Requirement ◽  
Chinese Han ◽  
Derivation Cohort ◽  
Dose Prediction ◽  
Low Intensity ◽  
Refinement Algorithm

SummaryPharmacogenetic (PG) dosing algorithms have been confirmed to predict warfarin therapeutic dose more accurately;however, most of them are based on standard intensity of warfarin anticoagulation, and their utility outside this range is limited. This study was designed to develop and validate a PG refinement algorithm in Chinese patients mainly under low-intensity warfarin anticoagulation. Consented Chinese-Han patients (n=310) under stable warfarin treatment were randomly divided into a derivation (n=207) and a validation cohort (n=103), with 83% and 80% of the patients under low-intensity anticoagulation, respectively. In the derivation cohort, a PG algorithm was constructed on the basis of genotypes (CYP2C9*3 and VKORC1–1639A/G) and clinical data. After integrating additional covariates of international normalised ratio (INR) values (INR on day 4 of therapy and target INR) and genotype of CYP4F2 (rs2108622), a PG refinement algorithm was established and explained 54% of warfarin dose variability. In the validation cohort, warfarin dose prediction was more accurate (p <0.01) with the PG refinement algorithm than with the PG algorithm and the fixed dose approach (3 mg/day). In the entire cohort, the PG refinement algorithm could accurately identify larger proportions of patients with lower dose requirement (≤2 mg/day) and higher dose requirement (≥4 mg/day) than did the PG algorithm. In conclusion, PG refinement algorithm integrating early INR response and three genotypes CYP2C9*3, VKORC1–1639A/G, CYP4F2 rs2108622) improves the accuracy of warfarin dose prediction in Chinese patients mainly under low-intensity anticoagulation.

Pharmacogenetic algorithm for predicting daily dose of warfarin in Caucasian patients of Czech origin

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Aleš Tomek ◽  
Tereza Růžičková ◽  
Vojtěch Kaplan ◽  
Zuzana Lacinová ◽  
Simona Kumstýřová ◽  
...  
Keyword(s):  
Validation Cohort ◽  
Warfarin Dose ◽  
Therapeutic Index ◽  
Coefficient Of Determination ◽  
Dose Prediction ◽  
Pharmacogenetic Algorithm ◽  
Daily Dose ◽  
Caucasian Patients ◽  
Variant Alleles ◽  
Initiation Of Therapy

Abstract Objectives Warfarin use is limited by a low therapeutic index and significant interindividual variability of the daily dose. The most important factor predicting daily warfarin dose is individual genotype, polymorphisms of genes CYP2C9 (warfarin metabolism) and VKORC1 (sensitivity for warfarin). Algorithms using clinical and genetic variables could predict the daily dose before the initiation of therapy. The aim of this study was to develop and validate an algorithm for the prediction of warfarin daily dose in Czech patients. Methods Detailed clinical data of patients with known and stable warfarin daily dose were collected. All patients were genotyped for polymorphisms in genes CYP2C9 and VKORC1. Results Included patients were divided into derivation (n=175) and validation (n=223) cohorts. The final algorithm includes the following variables: Age, height, weight, treatment with amiodarone and presence of variant alleles of genes CYP2C9 and VKORC1. The adjusted coefficient of determination is 72.4% in the derivation and 62.3% in the validation cohort (p<0.001). Conclusions Our validated algorithm for warfarin daily dose prediction in our Czech cohort had higher precision than other currently published algorithms. Pharmacogenetics of warfarin has the potential in the clinical practice in specialized centers.

Use of Pharmacogenetics and Clinical Factors To Predict the Maintenance Dose of Warfarin.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 550-550
Author(s):  
B. F. Gage ◽  
C. S. Eby ◽  
J. A. Johnson ◽  
M. J. Rieder ◽  
P. M. Ridker ◽  
...  
Keyword(s):  
African American ◽  
Warfarin Therapy ◽  
Validation Cohort ◽  
Pcr Amplification ◽  
Warfarin Dose ◽  
Regression Equation ◽  
Nucleotide Polymorphisms ◽  
Clinical Factors ◽  
Derivation Cohort ◽  
Unit Increase

Abstract Background Initiation of warfarin therapy using trial-and-error dosing can cause bleeding. Clinical factors explain only 20%–30% of the variability in the therapeutic dose of warfarin. Single nucleotide polymorphisms (SNPs) in the cytochrome P450 2C9 (CYP2C9) gene correlate with the clearance of S-warfarin and SNPs in the vitamin K epoxide reductase (VKORC1) gene predict warfarin sensitivity. We test the hypothesis that the combination of clinical and pharmacogenetic information can predict the therapeutic warfarin dose. Methods We collected DNA, demographic variables, laboratory values, and medication histories from patients taking warfarin. Subjects either attended an outpatient anticoagulation clinic or participated in the PREVENT (prevention of venous thromboembolism) study. After PCR amplification, we used Pyrosequencing® to genotype DNA regions for 2 coding CYP2C9 SNPs, *2 (C430T) and *3 (A1075C), and for 4 noncoding VKORC1 SNPs: C861A, A5808C, G6853C, and G9041A. Using multiple regression, we quantified the association between therapeutic warfarin dose and clinical and genetic factors in a derivation cohort of 900 participants and a validation cohort of 100 participants. Results The VKORC1 G6853C SNP was the first variable to enter the stepwise regression equation and was associated with a 27% decrease in the warfarin dose per allele in Caucasian patients. The VKORC1 A5808C SNP was associated with a 33% decrease per allele in warfarin dose in African-American patients. Other significant (p &lt; 0.05) predictors of the therapeutic warfarin dose, in order of entry into the regression equation and their effect on warfarin dose were: body surface area (+12% per SD increase), CYP2C9*3 (−33% per allele), CYP2C9*2 (−20% per allele), age (−7% per decade), target INR (+8% per 0.5 unit increase), amiodarone use (−24%), African-American race (+12%), smoker (+9%), and simvastatin or fluvastatin use (−5%). A dosing equation that included these pharmacogenetic and clinical factors explained 52% of the dose variability in derivation cohort and 55% of the variability in the validation cohort. Conclusions The therapeutic warfarin dose can be estimated from clinical and pharmacogenetic factors that can be obtained when warfarin is started. Use of this dosing equation has potential to aid in the prediction of an optimal warfarin dose, which may decrease the risk of bleeding during the initiation of warfarin therapy.

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

2020 ◽  
Vol 21 (14) ◽  
pp. 1021-1031
Author(s):  
Dongxu Wang ◽  
Da-Peng Dai ◽  
Hualan Wu ◽  
Jia Chong ◽  
You Lü ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Predictive Power ◽  
Warfarin Dose ◽  
Multivariate Regression Analysis ◽  
Chinese Patients ◽  
Chinese Han ◽  
Dosing Algorithm ◽  
Warfarin Dosing ◽  
Univariate Analyses

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.

scholarly journals Plasma miRNA profiles associated with stable warfarin dosage in Chinese patients

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9995
Author(s):  
Li Zhao ◽  
Jin Wang ◽  
Shaoxin Shi ◽  
Yuan Wu ◽  
Jumei Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Prediction Models ◽  
Comprehensive Evaluation ◽  
Warfarin Dose ◽  
Chinese Patients ◽  
Warfarin Dosage ◽  
Multivariate Logistic Regression ◽  
Chinese Han ◽  
Expression Levels ◽  
Plasma Mirnas

Background We used bioinformatic analysis and quantitative reverse transcription polymerase chain reaction (RT-qPCR) assays to investigate the association between plasma microRNAs (miRNAs) and stable warfarin dosage in a Chinese Han population. Methods Bioinformatics analysis was used to screen out potential warfarin dose-associated miRNAs. Three plasma miRNAs were validated in 99 samples by RT-qPCR. Kruskal–Wallis test and multivariate logistic regression were used to compare differences in plasma miRNAs expression levels between three warfarin dosage groups. Results There were significant between-group differences among the three dose groups for hsa-miR-133b expression (p = 0.005), but we observed an “n-shaped” dose-dependent curve rather than a linear relationship. Expression levels of hsa-miR-24-3p (p = 0.475) and hsa-miR-1276 (p = 0.558) were not significantly different in the multivariate logistic regression. Conclusion miRNAs have received extensive attention as ideal biomarkers and possible therapeutic targets for various diseases. However, they are not yet widely used in precision medicine. Our results indicate that hsa-miR-133b may be a possible reference factor for the warfarin dosage algorithm. These findings emphasize the importance of a comprehensive evaluation of complex relationships in warfarin dose prediction models and provide new avenues for future pharmacogenomics studies.

scholarly journals Pharmacogenetic warfarin dose refinements remain significantly influenced by genetic factors after one week of therapy

2012 ◽  
Vol 107 (02) ◽  
pp. 232-240 ◽  
Author(s):  
Petra Lenzini ◽  
Mia Wadelius ◽  
Andrea Jorgensen ◽  
Stephen Kimmel ◽  
Paul Ridker ◽  
...  
Keyword(s):  
Treatment Response ◽  
Genetic Factors ◽  
Validation Cohort ◽  
Warfarin Dose ◽  
Absolute Error ◽  
Clinical Algorithm ◽  
Response Index ◽  
Dose Variability ◽  
Index Treatment ◽  
Refinement Algorithm

SummaryBy 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 R2 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: R2= 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.

scholarly journals Prediction of Warfarin Dose in Pediatric Patients: An Evaluation of the Predictive Performance of Several Models

2016 ◽  
Vol 21 (3) ◽  
pp. 224-232
Author(s):  
Elizabeth Marek ◽  
Jeremiah D. Momper ◽  
Ronald N. Hines ◽  
Cheryl M. Takao ◽  
Joan C. Gill ◽  
...  
Keyword(s):  
Pediatric Patients ◽  
Prediction Models ◽  
Validation Cohort ◽  
Warfarin Dose ◽  
Predictive Ability ◽  
Predictive Performance ◽  
Optimal Dose ◽  
International Normalized Ratio ◽  
Multicenter Trial ◽  
Fixed Dose

OBJECTIVES: The objective of this study was to evaluate the performance of pediatric pharmacogenetic-based dose prediction models by using an independent cohort of pediatric patients from a multicenter trial. METHODS: Clinical and genetic data (CYP2C9 [cytochrome P450 2C9] and VKORC1 [vitamin K epoxide reductase]) were collected from pediatric patients aged 3 months to 17 years who were receiving warfarin as part of standard care at 3 separate clinical sites. The accuracy of 8 previously published pediatric pharmacogenetic-based dose models was evaluated in the validation cohort by comparing predicted maintenance doses to actual stable warfarin doses. The predictive ability was assessed by using the proportion of variance (R2), mean prediction error (MPE), and the percentage of predictions that fell within 20% of the actual maintenance dose. RESULTS: Thirty-two children reached a stable international normalized ratio and were included in the validation cohort. The pharmacogenetic-based warfarin dose models showed a proportion of variance ranging from 35% to 78% and an MPE ranging from −2.67 to 0.85 mg/day in the validation cohort. Overall, the model developed by Hamberg et al showed the best performance in the validation cohort (R2 = 78%; MPE = 0.15 mg/day) with 38% of the predictions falling within 20% of observed doses. CONCLUSIONS: Pharmacogenetic-based algorithms provide better predictions than a fixed-dose approach, although an optimal dose algorithm has not yet been developed.

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