Literature DB >> 1902764

An updated comparison of drug dosing methods. Part I: Phenytoin.

R D Pryka1, K A Rodvold, S M Erdman.   

Abstract

The relationship between a dose of phenytoin and the resultant serum concentration is difficult to predict, and numerous dosing methods have been developed to quantify the dose required to achieve a specific concentration. This review brings up to date the earlier article in the Journal regarding predictive algorithms, various pharmacokinetics-based dosing techniques and Bayesian feedback methods for phenytoin dosing. The latest data support the original conclusions that dosing methods for phenytoin which incorporate an individualised approach or Bayesian principles tend to offer results superior to those from predictive algorithms. Bayesian methods have the additional advantage of using only 1 serum concentration, obtained under either steady-state or non-steady-state conditions. There is still a need for future investigations that include prospective evaluations of predictive performance and cost-effectiveness data.

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Year:  1991        PMID: 1902764     DOI: 10.2165/00003088-199120030-00003

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  42 in total

1.  Clinical and electroencephalographic correlations with serum levels of diphenylhydanotin.

Authors:  F BUCHTHAL; O SVENSMARK; P J SCHILLER
Journal:  Arch Neurol       Date:  1960-06

2.  Clinical utility of a Bayesian dosing program for phenytoin.

Authors:  M D Privitera; R W Homan; T M Ludden; C C Peck; M R Vasko
Journal:  Ther Drug Monit       Date:  1989       Impact factor: 3.681

3.  A comparison of graphical nomogram methods with a computerized Bayesian analysis method in the interpretation of serum phenytoin concentrations.

Authors:  H Chrystyn; D H Morgan
Journal:  J Clin Hosp Pharm       Date:  1986-12

4.  A graphic method for predicting individual phenytoin levels in an office practice.

Authors:  F C Robinson; P R Mayer
Journal:  Ther Drug Monit       Date:  1982       Impact factor: 3.681

5.  New and simple method to predict dosage of drugs obeying simple Michaelis-Menten elimination kinetics and to distinguish such kinetics from simple first order and from parallel Michaelis-Menten and first order kinetics.

Authors:  J G Wagner
Journal:  Ther Drug Monit       Date:  1985       Impact factor: 3.681

6.  Nomographic estimation of time to reach steady-state serum concentration during phenytoin therapy.

Authors:  S Vozeh; F Follath
Journal:  Eur J Clin Pharmacol       Date:  1980-01       Impact factor: 2.953

7.  Phenytoin dosage requirements and pharmacokinetic variables.

Authors:  J W Taylor; M J Murphy; M J Berg; P J Perry; L W Lyon; T M Ludden
Journal:  Clin Pharm       Date:  1983 May-Jun

8.  A comparison of phenytoin dosing methods in private practice seizure patients.

Authors:  T E Welty; F C Robinson; P R Mayer
Journal:  Epilepsia       Date:  1986 Jan-Feb       Impact factor: 5.864

9.  Michaelis-Menten pharmacokinetics of diphenylhydantoin and application in the pediatric age patient.

Authors:  K Chiba; T Ishizaki; H Miura; K Minagawa
Journal:  J Pediatr       Date:  1980-03       Impact factor: 4.406

10.  Individual variation in daily dosage requirements for phenytoin sodium in patients with epilepsy.

Authors:  M H Barot; R H Grant; K K Maheendran; G E Mawer; B G Woodcock
Journal:  Br J Clin Pharmacol       Date:  1978-09       Impact factor: 4.335

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  3 in total

Review 1.  Bayesian forecasting in paediatric populations.

Authors:  M M Fernández de Gatta; M J García; J M Lanao; A Domínguez-Gil
Journal:  Clin Pharmacokinet       Date:  1996-11       Impact factor: 6.447

Review 2.  Optimisation of antiepileptic drug therapy. The importance of serum drug concentration monitoring.

Authors:  E Yukawa
Journal:  Clin Pharmacokinet       Date:  1996-08       Impact factor: 6.447

Review 3.  Pharmacokinetic optimisation of anticonvulsant therapy.

Authors:  A H Thomson; M J Brodie
Journal:  Clin Pharmacokinet       Date:  1992-09       Impact factor: 6.447

  3 in total

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