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Transformations of summary statistics as input in meta-analysis for linear dose-response models on a logarithmic scale: a methodology developed within EURRECA

BACKGROUND: To derive micronutrient recommendations in a scientifically sound way, it is important to obtain and analyse all published information on the association between micronutrient intake and biochemical proxies for micronutrient status using a systematic approach. Therefore, it is important...

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Autores principales: Souverein, Olga W, Dullemeijer, Carla, van `t Veer, Pieter, van der Voet, Hilko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3780718/
https://www.ncbi.nlm.nih.gov/pubmed/22533574
http://dx.doi.org/10.1186/1471-2288-12-57
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author Souverein, Olga W
Dullemeijer, Carla
van `t Veer, Pieter
van der Voet, Hilko
author_facet Souverein, Olga W
Dullemeijer, Carla
van `t Veer, Pieter
van der Voet, Hilko
author_sort Souverein, Olga W
collection PubMed
description BACKGROUND: To derive micronutrient recommendations in a scientifically sound way, it is important to obtain and analyse all published information on the association between micronutrient intake and biochemical proxies for micronutrient status using a systematic approach. Therefore, it is important to incorporate information from randomized controlled trials as well as observational studies as both of these provide information on the association. However, original research papers present their data in various ways. METHODS: This paper presents a methodology to obtain an estimate of the dose–response curve, assuming a bivariate normal linear model on the logarithmic scale, incorporating a range of transformations of the original reported data. RESULTS: The simulation study, conducted to validate the methodology, shows that there is no bias in the transformations. Furthermore, it is shown that when the original studies report the mean and standard deviation or the geometric mean and confidence interval the results are less variable compared to when the median with IQR or range is reported in the original study. CONCLUSIONS: The presented methodology with transformations for various reported data provides a valid way to estimate the dose–response curve for micronutrient intake and status using both randomized controlled trials and observational studies.
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spelling pubmed-37807182013-09-24 Transformations of summary statistics as input in meta-analysis for linear dose-response models on a logarithmic scale: a methodology developed within EURRECA Souverein, Olga W Dullemeijer, Carla van `t Veer, Pieter van der Voet, Hilko BMC Med Res Methodol Research Article BACKGROUND: To derive micronutrient recommendations in a scientifically sound way, it is important to obtain and analyse all published information on the association between micronutrient intake and biochemical proxies for micronutrient status using a systematic approach. Therefore, it is important to incorporate information from randomized controlled trials as well as observational studies as both of these provide information on the association. However, original research papers present their data in various ways. METHODS: This paper presents a methodology to obtain an estimate of the dose–response curve, assuming a bivariate normal linear model on the logarithmic scale, incorporating a range of transformations of the original reported data. RESULTS: The simulation study, conducted to validate the methodology, shows that there is no bias in the transformations. Furthermore, it is shown that when the original studies report the mean and standard deviation or the geometric mean and confidence interval the results are less variable compared to when the median with IQR or range is reported in the original study. CONCLUSIONS: The presented methodology with transformations for various reported data provides a valid way to estimate the dose–response curve for micronutrient intake and status using both randomized controlled trials and observational studies. BioMed Central 2012-04-25 /pmc/articles/PMC3780718/ /pubmed/22533574 http://dx.doi.org/10.1186/1471-2288-12-57 Text en Copyright © 2012 Souverein et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Souverein, Olga W
Dullemeijer, Carla
van `t Veer, Pieter
van der Voet, Hilko
Transformations of summary statistics as input in meta-analysis for linear dose-response models on a logarithmic scale: a methodology developed within EURRECA
title Transformations of summary statistics as input in meta-analysis for linear dose-response models on a logarithmic scale: a methodology developed within EURRECA
title_full Transformations of summary statistics as input in meta-analysis for linear dose-response models on a logarithmic scale: a methodology developed within EURRECA
title_fullStr Transformations of summary statistics as input in meta-analysis for linear dose-response models on a logarithmic scale: a methodology developed within EURRECA
title_full_unstemmed Transformations of summary statistics as input in meta-analysis for linear dose-response models on a logarithmic scale: a methodology developed within EURRECA
title_short Transformations of summary statistics as input in meta-analysis for linear dose-response models on a logarithmic scale: a methodology developed within EURRECA
title_sort transformations of summary statistics as input in meta-analysis for linear dose-response models on a logarithmic scale: a methodology developed within eurreca
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3780718/
https://www.ncbi.nlm.nih.gov/pubmed/22533574
http://dx.doi.org/10.1186/1471-2288-12-57
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