ArticleBMC medical informatics and decision making2015
A Bayesian decision support tool for efficient dose individualization of warfarin in adults and children.
Article in BMC medical informatics and decision making, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03797534 (Individualized Administration of Warfarin by Polymorphisms of VKORC1 and CYP2C9 Genes), which is not on this map. Cited by 22 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Individualized Administration of Warfarin by Polymorphisms of VKORC1 and CYP2C9 Genes:A Randomized Controlled Trial, Multi-center Trial
Who cites it
22 citing papers in PubMed, 64 citations in OpenAlex.
- Real-world clinical validation study: individualized warfarin dosing strategy integrating genetic polymorphisms and Bayesian.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- AI-assisted warfarin dose optimisation with CURATE.AI for clinical impact: Retrospective data analysis.Bioengineering & translational medicine · 2025Article
- Construction of warfarin population pharmacokinetics and pharmacodynamics model in Han population based on Bayesian method.Scientific reports · 2024Article
- Simulating clinical trials for model-informed precision dosing: using warfarin treatment as a use case.Frontiers in 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
- Long Short-Term Memory Network for Development and Simulation of Warfarin Dosing Model Based on Time Series Anticoagulant Data.Frontiers in cardiovascular medicine · 2022Article
- Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology.BMC medical informatics and decision making · 2020Article
- Development and Validation of a Population-Pharmacokinetic Model for Rurioctacog Alfa Pegol (AdynovateClinical pharmacokinetics · 2020Article
- The Prediction Model of Warfarin Individual Maintenance Dose for Patients Undergoing Heart Valve Replacement, Based on the Back Propagation Neural Network.Clinical drug investigation · 2020Article
- Gene-based anticoagulation regimens for an infant after mitral-valve replacement: A case report.Medicine · 2020Article
- Personalised Warfarin Dosing in Children Post-cardiac Surgery.Pediatric cardiology · 2019Observational
- Towards Personalized Antithrombotic Treatments: Focus on P2YClinical pharmacokinetics · 2019Review
- Routine clinical care data for population pharmacokinetic modeling: the case for Fanhdi/Alphanate in hemophilia A patients.Journal of pharmacokinetics and pharmacodynamics · 2019Article
- Relationship between warfarin dosage and international normalized ratio: a dose-response analysis and evaluation based on multicenter data.European journal of clinical pharmacology · 2019Article
- Handling interoccasion variability in model-based dose individualization using therapeutic drug monitoring data.British journal of clinical pharmacology · 2019Article
- Understanding and applying pharmacometric modelling and simulation in clinical practice and research.British journal of clinical pharmacology · 2017Review
- Pharmacogenomics in Pediatric Patients: Towards Personalized Medicine.Paediatric drugs · 2016Review
- Quantitative Systems Pharmacology: A Framework for Context.Current pharmacology reports · 2016Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWarfarin is the most widely prescribed anticoagulant for the prevention and treatment of thromboembolic events. Although highly effective, the use of warfarin is limited by a narrow therapeutic range combined with a more than ten-fold difference in the dose required for adequate anticoagulation in adults. An optimal dose that leads to a favourable balance between the wanted antithrombotic effect and the risk of bleeding as measured by the prothrombin time International Normalised Ratio (INR) must be found for each patient. A model describing the time-course of the INR response can be used to aid dose selection before starting therapy (a priori dose prediction) and after therapy has been initiated (a posteriori dose revision).
resultsIn this paper we describe a warfarin decision support tool. It was transferred from a population PKPD-model for warfarin developed in NONMEM to a platform independent tool written in Java. The tool proved capable of solving a system of differential equations that represent the pharmacokinetics and pharmacodynamics of warfarin with a performance comparable to NONMEM. To estimate an a priori dose the user enters information on body weight, age, baseline and target INR, and optionally CYP2C9 and VKORC1 genotype. By adding information about previous doses and INR observations, the tool will suggest a new dose a posteriori through Bayesian forecasting. Results are displayed as the predicted dose per day and per week, and graphically as the predicted INR curve. The tool can also be used to predict INR following any given dose regimen, e.g. a fixed or an individualized loading-dose regimen.
conclusionsWe believe that this type of mechanism-based decision support tool could be useful for initiating and maintaining warfarin therapy in the clinic. It will ensure more consistent dose adjustment practices between prescribers, and provide efficient and truly individualized warfarin dosing in both children and adults.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.