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Reconstructing 2 x 2 contingency tables from odds ratios using the Di Pietrantonj method: difficulties, constraints and impact in meta-analysis results

Authors

  • Areti Angeliki Veroniki,

    Corresponding author
    • Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
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  • Marios Pavlides,

    1. Centre for Statistical Science and Operational Research, Queen's University Belfast, Belfast, UK
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  • Nikolaos A Patsopoulos,

    1. Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
    2. Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts, USA
    3. Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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  • Georgia Salanti

    1. Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
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Correspondence to: Areti Angeliki Veroniki, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, Ioannina 45110, Greece.

E-mail: averonik@cc.uoi.gr

Abstract

A problem that is frequently encountered during the systematic review process is when studies that meet the inclusion criteria do not provide the appropriate numerical estimates to include in a meta-analysis. For dichotomous outcomes, a method has been suggested by Di Pietrantonj for reconstructing the 2 × 2 table when the Odds Ratio (OR), the Standard Error (SE(lnOR)) and the sample sizes are provided. The method produces two possible 2 × 2 tables; and to select the correct one, the Control Group Risk (CGR) is used. As CGR is typically unknown and only rounded figures of the OR and SE(lnOR) are provided, the accuracy of the reconstruction method varies. In this paper, we evaluate the performance of the method using simulated and empirical data. Small studies with large OR and CGR away from 50% are reconstructed satisfactorily, and the use of SE(lnOR) rounded to the third decimal rather than the second one improves the performance of the method. However, when CGR is unknown, its estimation from other studies is problematic as it exhibits high heterogeneity. Inclusion of an incorrectly reconstructed table in the meta-analysis may result in different summary effects. Reviewers that consider applying the method should be cautious about its impact in the meta-analysis. Copyright © 2012 John Wiley & Sons, Ltd.

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