Cargando…
Kinetic modelling of myocardial necrosis biomarkers offers an easier, reliable and more acceptable assessment of infarct size
Infarct size is a major prognostic factor in ST-segment elevation myocardial infarction (STEMI). It is often assessed using repeated blood sampling and the estimation of biomarker area under the concentration versus time curve (AUC) in translational research. We aimed at developing limited sampling...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423884/ https://www.ncbi.nlm.nih.gov/pubmed/32788683 http://dx.doi.org/10.1038/s41598-020-70501-4 |
_version_ | 1783570216462057472 |
---|---|
author | Chadet, Stéphanie Ternant, David Roubille, François Bejan-Angoulvant, Theodora Prunier, Fabrice Mewton, Nathan Paintaud, Gilles Ovize, Michel Dupuy, Anne Marie Angoulvant, Denis Ivanes, Fabrice |
author_facet | Chadet, Stéphanie Ternant, David Roubille, François Bejan-Angoulvant, Theodora Prunier, Fabrice Mewton, Nathan Paintaud, Gilles Ovize, Michel Dupuy, Anne Marie Angoulvant, Denis Ivanes, Fabrice |
author_sort | Chadet, Stéphanie |
collection | PubMed |
description | Infarct size is a major prognostic factor in ST-segment elevation myocardial infarction (STEMI). It is often assessed using repeated blood sampling and the estimation of biomarker area under the concentration versus time curve (AUC) in translational research. We aimed at developing limited sampling strategies (LSS) to accurately estimate biomarker AUC using only a limited number of blood samples in STEMI patients. This retrospective study was carried out on pooled data from five clinical trials of STEMI patients (TIMI blood flow 0/1) studies where repeated blood samples were collected within 72 h after admission to assess creatine kinase (CK), cardiac troponin I (cTnI) and muscle-brain CK (CK-MB). Biomarker kinetics was assessed using previously described biomarker kinetic models. A number of LSS models including combinations of 1 to 3 samples were developed to identify sampling times leading to the best estimation of AUC. Patients were randomly assigned to either learning (2/3) or validation (1/3) subsets. Descriptive and predictive performances of LSS models were compared using learning and validation subsets, respectively. An external validation cohort was used to validate the model and its applicability to different cTnI assays, including high-sensitive (hs) cTnI. 132 patients had full CK and cTnI dataset, 49 patients had CK-MB. For each biomarker, 180 LSS models were tested. Best LSS models were obtained for the following sampling times: T4–16 for CK, T8–T20 for cTnI and T8–T16 for CK-MB for 2-sample LSS; and T4–T16–T24 for CK, T4–T12–T20 for cTnI and T8–T16–T20 for CK-MB for 3-sample LSS. External validation was achieved on 103 anterior STEMI patients (TIMI flow 0/1), and the cTnI model applicability to recommended hs cTnI confirmed. Biomarker kinetics can be assessed with a limited number of samples using kinetic modelling. This opens the way for substantial simplification of future cardioprotection studies, more acceptable for the patients. |
format | Online Article Text |
id | pubmed-7423884 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-74238842020-08-13 Kinetic modelling of myocardial necrosis biomarkers offers an easier, reliable and more acceptable assessment of infarct size Chadet, Stéphanie Ternant, David Roubille, François Bejan-Angoulvant, Theodora Prunier, Fabrice Mewton, Nathan Paintaud, Gilles Ovize, Michel Dupuy, Anne Marie Angoulvant, Denis Ivanes, Fabrice Sci Rep Article Infarct size is a major prognostic factor in ST-segment elevation myocardial infarction (STEMI). It is often assessed using repeated blood sampling and the estimation of biomarker area under the concentration versus time curve (AUC) in translational research. We aimed at developing limited sampling strategies (LSS) to accurately estimate biomarker AUC using only a limited number of blood samples in STEMI patients. This retrospective study was carried out on pooled data from five clinical trials of STEMI patients (TIMI blood flow 0/1) studies where repeated blood samples were collected within 72 h after admission to assess creatine kinase (CK), cardiac troponin I (cTnI) and muscle-brain CK (CK-MB). Biomarker kinetics was assessed using previously described biomarker kinetic models. A number of LSS models including combinations of 1 to 3 samples were developed to identify sampling times leading to the best estimation of AUC. Patients were randomly assigned to either learning (2/3) or validation (1/3) subsets. Descriptive and predictive performances of LSS models were compared using learning and validation subsets, respectively. An external validation cohort was used to validate the model and its applicability to different cTnI assays, including high-sensitive (hs) cTnI. 132 patients had full CK and cTnI dataset, 49 patients had CK-MB. For each biomarker, 180 LSS models were tested. Best LSS models were obtained for the following sampling times: T4–16 for CK, T8–T20 for cTnI and T8–T16 for CK-MB for 2-sample LSS; and T4–T16–T24 for CK, T4–T12–T20 for cTnI and T8–T16–T20 for CK-MB for 3-sample LSS. External validation was achieved on 103 anterior STEMI patients (TIMI flow 0/1), and the cTnI model applicability to recommended hs cTnI confirmed. Biomarker kinetics can be assessed with a limited number of samples using kinetic modelling. This opens the way for substantial simplification of future cardioprotection studies, more acceptable for the patients. Nature Publishing Group UK 2020-08-12 /pmc/articles/PMC7423884/ /pubmed/32788683 http://dx.doi.org/10.1038/s41598-020-70501-4 Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chadet, Stéphanie Ternant, David Roubille, François Bejan-Angoulvant, Theodora Prunier, Fabrice Mewton, Nathan Paintaud, Gilles Ovize, Michel Dupuy, Anne Marie Angoulvant, Denis Ivanes, Fabrice Kinetic modelling of myocardial necrosis biomarkers offers an easier, reliable and more acceptable assessment of infarct size |
title | Kinetic modelling of myocardial necrosis biomarkers offers an easier, reliable and more acceptable assessment of infarct size |
title_full | Kinetic modelling of myocardial necrosis biomarkers offers an easier, reliable and more acceptable assessment of infarct size |
title_fullStr | Kinetic modelling of myocardial necrosis biomarkers offers an easier, reliable and more acceptable assessment of infarct size |
title_full_unstemmed | Kinetic modelling of myocardial necrosis biomarkers offers an easier, reliable and more acceptable assessment of infarct size |
title_short | Kinetic modelling of myocardial necrosis biomarkers offers an easier, reliable and more acceptable assessment of infarct size |
title_sort | kinetic modelling of myocardial necrosis biomarkers offers an easier, reliable and more acceptable assessment of infarct size |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423884/ https://www.ncbi.nlm.nih.gov/pubmed/32788683 http://dx.doi.org/10.1038/s41598-020-70501-4 |
work_keys_str_mv | AT chadetstephanie kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT ternantdavid kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT roubillefrancois kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT bejanangoulvanttheodora kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT prunierfabrice kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT mewtonnathan kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT paintaudgilles kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT ovizemichel kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT dupuyannemarie kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT angoulvantdenis kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize AT ivanesfabrice kineticmodellingofmyocardialnecrosisbiomarkersoffersaneasierreliableandmoreacceptableassessmentofinfarctsize |