Literature DB >> 8491059

Identification of patients with impaired hepatic drug metabolism using a limited sampling procedure for estimation of phenazone (antipyrine) pharmacokinetic parameters.

D Fabre1, F Bressolle, R Goméni, O Bouvet, A Dubois, C Raffanel, J C Gris, M Galtier.   

Abstract

Phenazone (antipyrine) 1g was given by short intravenous infusion to 62 study participants (10 healthy drug-free volunteers and 52 patients with chronic liver disease). A Bayesian approach was developed to determine the individual pharmacokinetic parameters of phenazone. Statistical characteristics of the population pharmacokinetic parameters were first evaluated for 30 patients. When combined with 1 plasma drug concentration from members of the second group, these led to a Bayesian estimation of individual pharmacokinetic parameters for the remaining 32 individuals. Total clearance computed by Bayesian estimation was compared with maximal likelihood estimation of this parameter, the classical procedure. No statistically significant differences were found. Performance of the developed methodology was evaluated by computing bias and precision. The mean error was 0.0477 L/h. The precision of the prediction of this parameter (0.155 L/h) remained lower than the interindividual standard deviation (0.765 L/h). This procedure enables the estimation of individual pharmacokinetic parameters for phenazone. In this study, numerous laboratory tests were performed. A highly significant correlation (p < 0.001) was found between phenazone clearance and the prothrombin time, albumin, gamma-globulin, factor V, antithrombin III, fibrinogen and total bilirubin. Discriminant analysis determined that protein, alkaline phosphatase, creatininaemia and gamma-globulin had more significant discriminating power and gave better prognostic results than those seen with the Child-Pugh test.

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Year:  1993        PMID: 8491059     DOI: 10.2165/00003088-199324040-00006

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


  37 in total

1.  The antipyrine test in clinical pharmacology: conceptions and misconceptions.

Authors:  E S Vesell
Journal:  Clin Pharmacol Ther       Date:  1979-09       Impact factor: 6.875

2.  A Bayesian feedback method of aminoglycoside dosing.

Authors:  M E Burton; D C Brater; P S Chen; R B Day; P J Huber; M R Vasko
Journal:  Clin Pharmacol Ther       Date:  1985-03       Impact factor: 6.875

Review 3.  Normal liver function. A basis for understanding hepatic disease.

Authors:  J K Corless; H M Middleton
Journal:  Arch Intern Med       Date:  1983-12

4.  Analysis of pharmacokinetic data using parametric models. II. Point estimates of an individual's parameters.

Authors:  L B Sheiner
Journal:  J Pharmacokinet Biopharm       Date:  1985-10

5.  Bayesian estimation and prediction of clearance in high-dose methotrexate infusions.

Authors:  A Iliadis; M Bachir-Raho; R Bruno; R Favre
Journal:  J Pharmacokinet Biopharm       Date:  1985-02

6.  Optimal sampling times for minimum variance of clearance determination.

Authors:  M Døssing; A Vølund; H E Poulsen
Journal:  Br J Clin Pharmacol       Date:  1983-02       Impact factor: 4.335

7.  Drugs as indicators of hepatic function.

Authors:  R A Branch
Journal:  Hepatology       Date:  1982 Jan-Feb       Impact factor: 17.425

8.  Evaluation of methods for estimating population pharmacokinetic parameters. II. Biexponential model and experimental pharmacokinetic data.

Authors:  L B Sheiner; S L Beal
Journal:  J Pharmacokinet Biopharm       Date:  1981-10

9.  Superiority of the Child-Pugh classification to quantitative liver function tests for assessing prognosis of liver cirrhosis.

Authors:  I Albers; H Hartmann; J Bircher; W Creutzfeldt
Journal:  Scand J Gastroenterol       Date:  1989-04       Impact factor: 2.423

10.  Antipyrine clearance per unit liver volume in cirrhotics with and without hepatocellular carcinoma indicating a correlation with histological change of the liver.

Authors:  S Noda; S Kawata; S Miyoshi; Y Minami; S Tarui
Journal:  Gastroenterol Jpn       Date:  1989-04
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  8 in total

Review 1.  Assessment of liver metabolic function. Clinical implications.

Authors:  J Brockmöller; I Roots
Journal:  Clin Pharmacokinet       Date:  1994-09       Impact factor: 6.447

Review 2.  Dose adjustment in patients with liver disease.

Authors:  Fabiola Delcò; Lydia Tchambaz; Raymond Schlienger; Jürgen Drewe; Stephan Krähenbühl
Journal:  Drug Saf       Date:  2005       Impact factor: 5.606

Review 3.  Role of population pharmacokinetics in drug development. A pharmaceutical industry perspective.

Authors:  E Samara; R Granneman
Journal:  Clin Pharmacokinet       Date:  1997-04       Impact factor: 6.447

Review 4.  Effect of hepatic insufficiency on pharmacokinetics and drug dosing.

Authors:  R K Verbeeck; Y Horsmans
Journal:  Pharm World Sci       Date:  1998-10

Review 5.  Pharmacokinetics and dosage adjustment in patients with hepatic dysfunction.

Authors:  Roger K Verbeeck
Journal:  Eur J Clin Pharmacol       Date:  2008-09-02       Impact factor: 2.953

6.  Antipyrine disposition in obesity: evidence for negligible effect of obesity on hepatic oxidative metabolism.

Authors:  Y Caraco; E Zylber-Katz; E M Berry; M Levy
Journal:  Eur J Clin Pharmacol       Date:  1995       Impact factor: 2.953

7.  Multiple-dose pharmacokinetics of pefloxacin in patients with hepatocellular deficiency.

Authors:  M Galtier; F Bressolle; J E de la Coussaye; R Gomeni; P Joubert; F Gény; A Dubois; C Raffanel; G Saissi; J J Eledjam
Journal:  Clin Pharmacokinet       Date:  1993-11       Impact factor: 6.447

8.  Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.

Authors:  Felix Day; Tugce Karaderi; Michelle R Jones; Cindy Meun; Chunyan He; Alex Drong; Peter Kraft; Nan Lin; Hongyan Huang; Linda Broer; Reedik Magi; Richa Saxena; Triin Laisk; Margrit Urbanek; M Geoffrey Hayes; Gudmar Thorleifsson; Juan Fernandez-Tajes; Anubha Mahajan; Benjamin H Mullin; Bronwyn G A Stuckey; Timothy D Spector; Scott G Wilson; Mark O Goodarzi; Lea Davis; Barbara Obermayer-Pietsch; André G Uitterlinden; Verneri Anttila; Benjamin M Neale; Marjo-Riitta Jarvelin; Bart Fauser; Irina Kowalska; Jenny A Visser; Marianne Andersen; Ken Ong; Elisabet Stener-Victorin; David Ehrmann; Richard S Legro; Andres Salumets; Mark I McCarthy; Laure Morin-Papunen; Unnur Thorsteinsdottir; Kari Stefansson; Unnur Styrkarsdottir; John R B Perry; Andrea Dunaif; Joop Laven; Steve Franks; Cecilia M Lindgren; Corrine K Welt
Journal:  PLoS Genet       Date:  2018-12-19       Impact factor: 6.020

  8 in total

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