Phenytoin dosage predictions in paediatric patients. 1989

G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
School of Pharmacy, University of Maryland, Baltimore.

Phenytoin dosing in paediatric patients is complicated both by alterations in patient requirements due to growth and maturation changes and by the capacity-limited characteristics of phenytoin metabolism. This study examines 2 pharmacokinetic methods to adjust phenytoin dosage based on a single dosing-rate/steady-state serum phenytoin concentration pair. A Bayesian forecaster and a fixed parameter [rate of metabolism (Vmax)] method were examined with previously published sets of a priori parameter estimates. The fixed Vmax method was utilised with the parameter derived from native Japanese (method 1), US Caucasian (method 2) and European (method 3) patients. The Bayesian forecaster used a priori parameter estimates obtained from native Japanese (method 4) and European (method 5) patients. Each method was examined retrospectively in 34 paediatric patients with a total of 48 predictions possible. Measures of absolute predictability, bias (mean error, % dose) and precision (root mean squared error, % dose), were -3.58/12.2, -1.51/12.2, 4.06/9.96, -4.38/13.2, and -3.10/11.5, for methods 1, 2, 3, 4 and 5, respectively. There was no significant difference among the 5 methods. However, the Bayesian algorithm tended to be more robust over a broad range of situations, providing predictions in all cases. The fixed Vmax methods could not provide predictions in every case. Finally, all methods had a significant number of overpredictions of dosage. Poorer results were observed when prediction of steady-state serum concentrations were performed, partly due to the retrospective nature of the study. We conclude that close monitoring of patients, regardless of the method chosen to adjust dosage, is recommended.

UI MeSH Term Description Entries
D007223 Infant A child between 1 and 23 months of age. Infants
D007231 Infant, Newborn An infant during the first 28 days after birth. Neonate,Newborns,Infants, Newborn,Neonates,Newborn,Newborn Infant,Newborn Infants
D007564 Japan A country in eastern Asia, island chain between the North Pacific Ocean and the Sea of Japan, east of the Korean Peninsula. The capital is Tokyo. Bonin Islands
D010672 Phenytoin An anticonvulsant that is used to treat a wide variety of seizures. It is also an anti-arrhythmic and a muscle relaxant. The mechanism of therapeutic action is not clear, although several cellular actions have been described including effects on ion channels, active transport, and general membrane stabilization. The mechanism of its muscle relaxant effect appears to involve a reduction in the sensitivity of muscle spindles to stretch. Phenytoin has been proposed for several other therapeutic uses, but its use has been limited by its many adverse effects and interactions with other drugs. Diphenylhydantoin,Fenitoin,Phenhydan,5,5-Diphenylhydantoin,5,5-diphenylimidazolidine-2,4-dione,Antisacer,Difenin,Dihydan,Dilantin,Epamin,Epanutin,Hydantol,Phenytoin Sodium,Sodium Diphenylhydantoinate,Diphenylhydantoinate, Sodium
D002648 Child A person 6 to 12 years of age. An individual 2 to 5 years old is CHILD, PRESCHOOL. Children
D002675 Child, Preschool A child between the ages of 2 and 5. Children, Preschool,Preschool Child,Preschool Children
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000293 Adolescent A person 13 to 18 years of age. Adolescence,Youth,Adolescents,Adolescents, Female,Adolescents, Male,Teenagers,Teens,Adolescent, Female,Adolescent, Male,Female Adolescent,Female Adolescents,Male Adolescent,Male Adolescents,Teen,Teenager,Youths
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D014481 United States A country in NORTH AMERICA between CANADA and MEXICO.

Related Publications

G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
February 1997, Journal of clinical pharmacy and therapeutics,
G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
January 1989, Clinical pharmacy,
G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
May 1978, Journal of neurology, neurosurgery, and psychiatry,
G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
November 1998, Pediatrics,
G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
May 1978, Neurology,
G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
August 1973, Lancet (London, England),
G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
August 1973, Lancet (London, England),
G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
August 1975, Lancet (London, England),
G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
January 1983, Clinical pharmacokinetics,
G J Yuen, and P T Latimer, and L C Littlefield, and R W Mackey
August 1977, Age and ageing,
Copied contents to your clipboard!