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Infliximab in paediatric inflammatory bowel disease: External evaluation of population pharmacokinetic models.

Authors :
Heikal, Omnia Salah
van Rheenen, Patrick F.
Touw, Daan J.
Kosterink, Jos G. W.
Maurer, Marina
Koomen, Jeroen V.
Chelle, Pierre
Mian, Paola
Source :
British Journal of Clinical Pharmacology; Sep2024, Vol. 90 Issue 9, p2200-2214, 15p
Publication Year :
2024

Abstract

Aims: Use of infliximab (IFX) has improved outcomes in children with inflammatory bowel disease (IBD). However, a proportion of patients does not respond to IFX or loses response over time. Population pharmacokinetic (PopPK) modelling is a promising approach for IFX dose optimization, but with the increasing number of PopPK models in literature, model evaluation is essential. The aims of this study are: (i) to validate the predictive performance of existing IFX PopPK models using a cohort of children with IBD; and (ii) to perform a Bayesian estimation of the most suitable model to predict the next IFX concentrations. Methods: PubMed was searched for IFX PopPK models in children. Selected models were rebuilt and analysed using R. Model performance was assessed through goodness‐of‐fit‐plots, residuals against time, prediction error and prediction‐corrected visual predictive checks. The validation cohort consisted of 73 children with IBD who were treated with IFX in our centre between 2017 and 2023 (340 IFX measurements). Results: We identified 9 PopPK models. Model bias for individual predicted values ranged from −9.29% to 8.01% compared to bias for population predicted values. The model by Vande Casteele et al. demonstrated superior performance (individual predicted bias 2.13, population predicted bias −6.11); upon Bayesian estimation, it predicted induction trough levels with median error of 12.95% but had a median error of −69% predicting maintenance concentrations. Conclusion: The model by Vande Casteele et al. displayed superior performance in initial evaluations but had a high error in estimating next IFX levels and can only be used in practice to predict induction levels. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03065251
Volume :
90
Issue :
9
Database :
Complementary Index
Journal :
British Journal of Clinical Pharmacology
Publication Type :
Academic Journal
Accession number :
179320553
Full Text :
https://doi.org/10.1111/bcp.16126