Literature DB >> 12548142

A Bayesian method based on clotting factor activity for the prediction of maintenance warfarin dosage regimens.

Maria Pitsiu1, Eva M Parker, Leon Aarons, Malcolm Rowland.   

Abstract

A Bayesian algorithm, employing a population pharmacokinetic-pharmacodynamic model, for the effective and rapid prediction of warfarin maintenance dosing requirements was developed. The algorithm was evaluated prospectively in five healthy volunteers who were given a 15-mg single dose of racemic warfarin. Based on previous population pharmacokinetic and pharmacodynamic parameters and factor VII response measurements taken during the first 48 hours, dosage regimens to achieve a subtherapeutic degree of anticoagulation (50% of normal) were determined. Three factor VII response measurements were sufficient to determine dosing requirements in the five volunteers. The advantage of the algorithm is that it does not require warfarin concentration measurements and uses non-steady-state data.

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Year:  2003        PMID: 12548142     DOI: 10.1097/00007691-200302000-00005

Source DB:  PubMed          Journal:  Ther Drug Monit        ISSN: 0163-4356            Impact factor:   3.681


  8 in total

1.  A Joint Model for Vitamin K-Dependent Clotting Factors and Anticoagulation Proteins.

Authors:  Qing Xi Ooi; Daniel F B Wright; R Campbell Tait; Geoffrey K Isbister; Stephen B Duffull
Journal:  Clin Pharmacokinet       Date:  2017-12       Impact factor: 6.447

2.  Assessing the relative potency of (S)- and (R)-warfarin with a new PK-PD model, in relation to VKORC1 genotypes.

Authors:  Myriam Ferrari; Vittorio Pengo; Massimiliano Barolo; Fabrizio Bezzo; Roberto Padrini
Journal:  Eur J Clin Pharmacol       Date:  2017-04-05       Impact factor: 2.953

3.  Development of a bayesian forecasting method for warfarin dose individualization.

Authors:  Daniel F B Wright; Stephen B Duffull
Journal:  Pharm Res       Date:  2011-02-08       Impact factor: 4.200

4.  Different risks of hemorrhage in patients with elevated international normalized ratio from chronic liver disease versus warfarin therapy, a population-based retrospective cohort study.

Authors:  Amber Afzal; Brian F Gage; Luo Suhong; Martin W Schoen; Kevin Korenblat; Kristen M Sanfilippo
Journal:  J Thromb Haemost       Date:  2022-05-26       Impact factor: 16.036

5.  A Bayesian dose-individualization method for warfarin.

Authors:  Daniel F B Wright; Stephen B Duffull
Journal:  Clin Pharmacokinet       Date:  2013-01       Impact factor: 6.447

6.  Glucuronidation of monohydroxylated warfarin metabolites by human liver microsomes and human recombinant UDP-glucuronosyltransferases.

Authors:  Agnieszka Zielinska; Cheryl F Lichti; Stacie Bratton; Neil C Mitchell; Anna Gallus-Zawada; Vi-Huyen Le; Moshe Finel; Grover P Miller; Anna Radominska-Pandya; Jeffery H Moran
Journal:  J Pharmacol Exp Ther       Date:  2007-10-05       Impact factor: 4.030

7.  The Clinical Pharmacokinetics and Pharmacodynamics of Warfarin When Combined with Compound Danshen: A Case Study for Combined Treatment of Coronary Heart Diseases with Atrial Fibrillation.

Authors:  Chunxiao Lv; Changxiao Liu; Zhuhua Yao; Xiumei Gao; Lanjun Sun; Jia Liu; Haibo Song; Ziqiang Li; Xi Du; Jinxia Sun; Yanfen Li; Kui Ye; Ruihua Wang; Yuhong Huang
Journal:  Front Pharmacol       Date:  2017-11-21       Impact factor: 5.810

8.  A factor VII-based method for the prediction of anticoagulant response to warfarin.

Authors:  Qing-Xi Ooi; Daniel F B Wright; Geoffrey K Isbister; Stephen B Duffull
Journal:  Sci Rep       Date:  2018-08-13       Impact factor: 4.379

  8 in total

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