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Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study

Modeling of retrospectively collected multi-center data of a rare disease in pediatrics is challenging because laboratory data can stem from several decades measured with different assays. Here we present a retrospective pharmacometrics (PMX) based data analysis of the rare disease congenital hypoth...

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Autores principales: Koch, Gilbert, Steffens, Britta, Leroux, Stephanie, Gotta, Verena, Schropp, Johannes, Gächter, Pascal, Bachmann, Freya, Welzel, Tatjana, Janner, Marco, L’Allemand, Dagmar, Konrad, Daniel, Szinnai, Gabor, Pfister, Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8405503/
https://www.ncbi.nlm.nih.gov/pubmed/34117565
http://dx.doi.org/10.1007/s10928-021-09765-w
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author Koch, Gilbert
Steffens, Britta
Leroux, Stephanie
Gotta, Verena
Schropp, Johannes
Gächter, Pascal
Bachmann, Freya
Welzel, Tatjana
Janner, Marco
L’Allemand, Dagmar
Konrad, Daniel
Szinnai, Gabor
Pfister, Marc
author_facet Koch, Gilbert
Steffens, Britta
Leroux, Stephanie
Gotta, Verena
Schropp, Johannes
Gächter, Pascal
Bachmann, Freya
Welzel, Tatjana
Janner, Marco
L’Allemand, Dagmar
Konrad, Daniel
Szinnai, Gabor
Pfister, Marc
author_sort Koch, Gilbert
collection PubMed
description Modeling of retrospectively collected multi-center data of a rare disease in pediatrics is challenging because laboratory data can stem from several decades measured with different assays. Here we present a retrospective pharmacometrics (PMX) based data analysis of the rare disease congenital hypothyroidism (CH) in newborns and infants. Our overall aim is to develop a model that can be applied to optimize dosing in this pediatric patient population since suboptimal treatment of CH during the first 2 years of life is associated with a reduced intelligence quotient between 10 and 14 years. The first goal is to describe a retrospectively collected dataset consisting of 61 newborns and infants with CH up to 2 years of age. Overall, 505 measurements of free thyroxine (FT4) and 510 measurements of thyrotropin or thyroid-stimulating hormone were available from patients receiving substitution treatment with levothyroxine (LT4). The second goal is to introduce a scale/location-scale normalization method to merge available FT4 measurements since 34 different postnatal age- and assay-specific laboratory reference ranges were applied. This method takes into account the change of the distribution of FT4 values over time, i.e. a transformation from right-skewed towards normality during LT4 treatment. The third goal is to develop a practical and useful PMX model for LT4 treatment to characterize FT4 measurements, which is applicable within a clinical setting. In summary, a time-dependent normalization method and a practical PMX model are presented. Since there is no on-going or planned development of new pharmacological approaches for CH, PMX based modeling and simulation can be leveraged to personalize dosing with the goal to enhance longer-term neurological outcome in children with the rare disease CH. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10928-021-09765-w.
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spelling pubmed-84055032021-09-09 Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study Koch, Gilbert Steffens, Britta Leroux, Stephanie Gotta, Verena Schropp, Johannes Gächter, Pascal Bachmann, Freya Welzel, Tatjana Janner, Marco L’Allemand, Dagmar Konrad, Daniel Szinnai, Gabor Pfister, Marc J Pharmacokinet Pharmacodyn Original Paper Modeling of retrospectively collected multi-center data of a rare disease in pediatrics is challenging because laboratory data can stem from several decades measured with different assays. Here we present a retrospective pharmacometrics (PMX) based data analysis of the rare disease congenital hypothyroidism (CH) in newborns and infants. Our overall aim is to develop a model that can be applied to optimize dosing in this pediatric patient population since suboptimal treatment of CH during the first 2 years of life is associated with a reduced intelligence quotient between 10 and 14 years. The first goal is to describe a retrospectively collected dataset consisting of 61 newborns and infants with CH up to 2 years of age. Overall, 505 measurements of free thyroxine (FT4) and 510 measurements of thyrotropin or thyroid-stimulating hormone were available from patients receiving substitution treatment with levothyroxine (LT4). The second goal is to introduce a scale/location-scale normalization method to merge available FT4 measurements since 34 different postnatal age- and assay-specific laboratory reference ranges were applied. This method takes into account the change of the distribution of FT4 values over time, i.e. a transformation from right-skewed towards normality during LT4 treatment. The third goal is to develop a practical and useful PMX model for LT4 treatment to characterize FT4 measurements, which is applicable within a clinical setting. In summary, a time-dependent normalization method and a practical PMX model are presented. Since there is no on-going or planned development of new pharmacological approaches for CH, PMX based modeling and simulation can be leveraged to personalize dosing with the goal to enhance longer-term neurological outcome in children with the rare disease CH. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10928-021-09765-w. Springer US 2021-06-11 2021 /pmc/articles/PMC8405503/ /pubmed/34117565 http://dx.doi.org/10.1007/s10928-021-09765-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Paper
Koch, Gilbert
Steffens, Britta
Leroux, Stephanie
Gotta, Verena
Schropp, Johannes
Gächter, Pascal
Bachmann, Freya
Welzel, Tatjana
Janner, Marco
L’Allemand, Dagmar
Konrad, Daniel
Szinnai, Gabor
Pfister, Marc
Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study
title Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study
title_full Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study
title_fullStr Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study
title_full_unstemmed Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study
title_short Modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study
title_sort modeling of levothyroxine in newborns and infants with congenital hypothyroidism: challenges and opportunities of a rare disease multi-center study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8405503/
https://www.ncbi.nlm.nih.gov/pubmed/34117565
http://dx.doi.org/10.1007/s10928-021-09765-w
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