ArticleClinical pharmacokinetics2013
A Bayesian dose-individualization method for warfarin.
Article in Clinical pharmacokinetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 47 citations in OpenAlex.
- Narrow Therapeutic Index Drugs: Regulatory Frameworks, Bioequivalence, and Model-Informed Precision Dosing.Pharmaceutics · 2026Review
- Real-world clinical validation study: individualized warfarin dosing strategy integrating genetic polymorphisms and Bayesian.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Construction of warfarin population pharmacokinetics and pharmacodynamics model in Han population based on Bayesian method.Scientific reports · 2024Article
- Deriving mechanism-based pharmacodynamic models by reducing quantitative systems pharmacology models: An application to warfarin.CPT: pharmacometrics & systems pharmacology · 2023Article
- Application of a warfarin dosing calculator to guide individualized dosingFrontiers in pharmacology · 2023Article
- Article
- Control-Relevant Adaptive Personalized Modeling From Limited Clinical Data for Precise Warfarin Management.IEEE open journal of engineering in medicine and biology · 2022Article
- Evaluation of pharmacogenomics and hepatic nuclear imaging-related covariates by population pharmacokinetic models of irinotecan and its metabolites.European journal of clinical pharmacology · 2022Article
- Warfarin maintenance dose prediction for Chinese after heart valve replacement by a feedforward neural network with equal stratified sampling.Scientific reports · 2021Article
- Effect of Protein Binding on Exposure of Unbound and Total Mycophenolic Acid: A Population Pharmacokinetic Analysis in Chinese Adult Kidney Transplant Recipients.Frontiers in pharmacology · 2020Article
- A factor VII-based method for the prediction of anticoagulant response to warfarin.Scientific reports · 2018Article
- A Joint Model for Vitamin K-Dependent Clotting Factors and Anticoagulation Proteins.Clinical pharmacokinetics · 2017Article
- Evaluation of Concomitant Antiretrovirals and CYP2C9/CYP2C19 Polymorphisms on the Pharmacokinetics of Etravirine.Clinical pharmacokinetics · 2017Article
- A Nonparametric Method to Optimize Initial Drug Dosing and Attainment of a Target Exposure Interval: Concepts and Application to Busulfan in Pediatrics.Clinical pharmacokinetics · 2017Article
- Pediatric Clinical Pharmacology of Voriconazole: Role of Pharmacokinetic/Pharmacodynamic Modeling in Pharmacotherapy.Clinical pharmacokinetics · 2016Review
- Effects of VKORC1 Genetic Polymorphisms on Warfarin Maintenance Dose Requirement in a Chinese Han Population.Medical science monitor : international medical journal of experimental and clinical research · 2015Article
- How to manage warfarin therapy.Australian prescriber · 2015Review
- Quantification of the Forgiveness of Drugs to Imperfect Adherence.CPT: pharmacometrics & systems pharmacology · 2015Article
- A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children.BMC medical informatics and decision making · 2015Article
- Optimal sampling of antipsychotic medicines: a pharmacometric approach for clinical practice.British journal of clinical pharmacology · 2014Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWarfarin is a difficult drug to dose accurately and safely due to large inter-individual variability in dose requirements. Current dosing strategies appear to be sub-optimal, with reports indicating that patients achieve international normalized ratios (INRs) within the therapeutic range only 40-65 % of the time. The consequences of poor INR control are potentially severe with INRs below 2 carrying an increased risk of clotting while INRs >4 increase the risk of major bleeding events. Bayesian forecasting methods have the potential to improve INR control.
aimsThe aims of this study were to (1) prospectively assess the predictive performance of a Bayesian dosing method for warfarin implemented in TCIWorks; and (2) determine the expected time in the therapeutic range (TTR) of INRs predicted using TCIWorks.
methodsPatients who were initiating warfarin therapy were prospectively recruited from Dunedin Hospital, Dunedin, New Zealand. Warfarin doses were entered into TCIWorks from the first day of therapy until a stable steady-state INR (INR(ss)) was achieved. The predicted INR(ss) values were determined using the first zero to six serially collected INR observations. Observed and predicted INR(ss) values were compared using measures of bias (mean prediction error [MPE]) and imprecision (root mean square error [RMSE]). The TTR was determined by calculating the percentage of predicted INR(ss) values between 2 and 3 when zero to six serially collected INR observations were available.
resultsA total of 55 patients were recruited between March and November 2011. When no observed INR values were available the resulting INR(ss) predictions were positively biased (MPE 0.52 [95 % CI 0.30, 0.73]); however, this disappeared once observed INR values were entered into TCIWorks. The precision of the predicted INR(ss) values improved dramatically once three or more observed INR values were available (RMSE <0.53) compared with no INRs (RMSE 0.96). These results suggest that TCIWorks will be effective at maintaining the INR within the therapeutic INR range (2-3) 65 % of the time when three INR measurements are available and 80 % of the time when six INR measurements are available.
conclusionThe TCIWorks warfarin dosing method produced accurate and precise INR(ss) predictions. We predict that the method will provide an INR value within the therapeutic range 65-80 % of the time once three or more INR observations are available, making this a useful tool for clinicians and warfarin clinics. Further research to assess the impact of this method on long-term INR control is warranted.
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