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Metabolomics for Prediction of Relapse in Graves' Disease: Observational Pilot Study
Background: There is a lack of biochemical markers for early prediction of relapse in patients with Graves' disease [GD], which may help to direct treatment decisions. We assessed the prognostic ability of a high-throughput proton NMR metabolomic profile to predict relapse in a well characteriz...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6199355/ https://www.ncbi.nlm.nih.gov/pubmed/30386302 http://dx.doi.org/10.3389/fendo.2018.00623 |
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author | Struja, Tristan Eckart, Andreas Kutz, Alexander Huber, Andreas Neyer, Peter Kraenzlin, Marius Mueller, Beat Meier, Christian Bernasconi, Luca Schuetz, Philipp |
author_facet | Struja, Tristan Eckart, Andreas Kutz, Alexander Huber, Andreas Neyer, Peter Kraenzlin, Marius Mueller, Beat Meier, Christian Bernasconi, Luca Schuetz, Philipp |
author_sort | Struja, Tristan |
collection | PubMed |
description | Background: There is a lack of biochemical markers for early prediction of relapse in patients with Graves' disease [GD], which may help to direct treatment decisions. We assessed the prognostic ability of a high-throughput proton NMR metabolomic profile to predict relapse in a well characterized cohort of GD patients. Methods: Observational study investigating patients presenting with GD at a Swiss hospital endocrine referral center and an associated endocrine outpatient clinic. We measured 227 metabolic markers in the blood of patients before treatment initiation. Main outcome was relapse of hyperthyroidism within 18 months of stopping anti-thyroid drugs. We used ROC analysis with AUC to assess discrimination. Results: Of 69 included patients 18 (26%) patients had a relapse of disease. The clinical GREAT score had an AUC of 0.68 (95% CI 0.63–0.70) to predict relapse. When looking at the metabolomic markers, univariate analysis revealed pyruvate and triglycerides in medium VLDL as predictors with AUCs of 0.73 (95% CI 0.58–0.84) and 0.67 (95% CI 0.53–0.80), respectively. All other metabolomic markers had lower AUCs. Conclusion: Overall, metabolomic markers in our pilot study had low to moderate prognostic potential for prediction of relapse of GD, with pyruvate and triglycerides being candidates with acceptable discriminatory abilities. Our data need validation in future larger trials. |
format | Online Article Text |
id | pubmed-6199355 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61993552018-11-01 Metabolomics for Prediction of Relapse in Graves' Disease: Observational Pilot Study Struja, Tristan Eckart, Andreas Kutz, Alexander Huber, Andreas Neyer, Peter Kraenzlin, Marius Mueller, Beat Meier, Christian Bernasconi, Luca Schuetz, Philipp Front Endocrinol (Lausanne) Endocrinology Background: There is a lack of biochemical markers for early prediction of relapse in patients with Graves' disease [GD], which may help to direct treatment decisions. We assessed the prognostic ability of a high-throughput proton NMR metabolomic profile to predict relapse in a well characterized cohort of GD patients. Methods: Observational study investigating patients presenting with GD at a Swiss hospital endocrine referral center and an associated endocrine outpatient clinic. We measured 227 metabolic markers in the blood of patients before treatment initiation. Main outcome was relapse of hyperthyroidism within 18 months of stopping anti-thyroid drugs. We used ROC analysis with AUC to assess discrimination. Results: Of 69 included patients 18 (26%) patients had a relapse of disease. The clinical GREAT score had an AUC of 0.68 (95% CI 0.63–0.70) to predict relapse. When looking at the metabolomic markers, univariate analysis revealed pyruvate and triglycerides in medium VLDL as predictors with AUCs of 0.73 (95% CI 0.58–0.84) and 0.67 (95% CI 0.53–0.80), respectively. All other metabolomic markers had lower AUCs. Conclusion: Overall, metabolomic markers in our pilot study had low to moderate prognostic potential for prediction of relapse of GD, with pyruvate and triglycerides being candidates with acceptable discriminatory abilities. Our data need validation in future larger trials. Frontiers Media S.A. 2018-10-17 /pmc/articles/PMC6199355/ /pubmed/30386302 http://dx.doi.org/10.3389/fendo.2018.00623 Text en Copyright © 2018 Struja, Eckart, Kutz, Huber, Neyer, Kraenzlin, Mueller, Meier, Bernasconi and Schuetz. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Struja, Tristan Eckart, Andreas Kutz, Alexander Huber, Andreas Neyer, Peter Kraenzlin, Marius Mueller, Beat Meier, Christian Bernasconi, Luca Schuetz, Philipp Metabolomics for Prediction of Relapse in Graves' Disease: Observational Pilot Study |
title | Metabolomics for Prediction of Relapse in Graves' Disease: Observational Pilot Study |
title_full | Metabolomics for Prediction of Relapse in Graves' Disease: Observational Pilot Study |
title_fullStr | Metabolomics for Prediction of Relapse in Graves' Disease: Observational Pilot Study |
title_full_unstemmed | Metabolomics for Prediction of Relapse in Graves' Disease: Observational Pilot Study |
title_short | Metabolomics for Prediction of Relapse in Graves' Disease: Observational Pilot Study |
title_sort | metabolomics for prediction of relapse in graves' disease: observational pilot study |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6199355/ https://www.ncbi.nlm.nih.gov/pubmed/30386302 http://dx.doi.org/10.3389/fendo.2018.00623 |
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