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Open Access Research article

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

Olga W Souverein1*, Carla Dullemeijer1, Pieter van `t Veer1 and Hilko van der Voet2

Author Affiliations

1 Division of Human Nutrition, Wageningen University and Research Centre, P.O. Box 8129, 6700, EV Wageningen, the Netherlands

2 Biometris, Wageningen University and Research Centre, P.O. Box 100, 6700, AC Wageningen, the Netherlands

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BMC Medical Research Methodology 2012, 12:57  doi:10.1186/1471-2288-12-57

Published: 25 April 2012

Abstract

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.

Keywords:
Methodology; Dose–response; Meta-analysis; EURRECA