Evidence map›Paper›PMID 30617957›Full record

ArticleEuropean journal of drug metabolism and pharmacokinetics2019

Population Pharmacokinetic Modelling of Pyrazinamide and Pyrazinoic Acid in Patients with Multi-Drug Resistant Tuberculosis.

Pierre Mugabo, Mwila Mulubwa

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Article in European journal of drug metabolism and pharmacokinetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Trial
  2. Article
  3. Role of therapeutic drug monitoring in the treatment of multi-drug resistant tuberculosis.Journal of clinical tuberculosis and other mycobacterial diseases · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Pierre MugaboSchool of Pharmacy, University of the Western Cape, Private Bag X17, Bellville, 7535, Cape Town, South Africa. pmugabo@uwc.ac.za.ORCID http://orcid.org/0000-0001-5653-0551
Mwila MulubwaSchool of Pharmacy, University of the Western Cape, Private Bag X17, Bellville, 7535, Cape Town, South Africa.ORCID http://orcid.org/0000-0003-2404-9717

Funding

South African Medical Research Council Self Initiated Research Grant 2017
6 · The paper itself

Abstract

BACKGROUND AND

objectivesPyrazinamide, a drug used in the regimen for the treatment of drug-sensitive tuberculosis, is also used for the treatment of multidrug-resistant tuberculosis (MDR-TB). We aimed to describe the population pharmacokinetics of pyrazinamide and its major metabolite, pyrazinoic acid, in patients with MDR-TB and characterise the effects of demographic variables.

methodsThis was a non-randomised clinical study involving 51 adult patients admitted for the intensive phase of MDR-TB treatment. Blood samples were collected at pre-dose and at 0.5, 1, 1.5, 2, 3, 4, 8, 16 and 24 h after drug administration. Plasma concentrations of pyrazinamide and pyrazinoic acid were analysed using a validated LC-MS/MS method. Nonlinear mixed-effects modelling using Monolix 2018R1 software was employed to estimate population pharmacokinetic parameters.

resultsA one-compartment pharmacokinetic model with transit compartment absorption process and first-order elimination best described the pyrazinamide and pyrazinoic acid concentration-time data. The estimated population pharmacokinetic parameters were 0.7 h, 3.38 h

conclusionsThe developed population pharmacokinetic model adequately described the disposition of pyrazinamide and pyrazinoic acid and can be useful for dose determination of pyrazinamide in patients with MDR-TB.

Indexed as

AdolescentAdultAntitubercular AgentsChromatography, LiquidFemaleHumansMaleMiddle AgedPyrazinamideTandem Mass SpectrometryTuberculosis, Multidrug-ResistantYoung AdultAntitubercular AgentsPyrazinamidepyrazinoic acid

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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.