Literature DB >> 26053541

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

Areti Angeliki Veroniki1, Marios Pavlides2, Nikolaos A Patsopoulos3,4,5, Georgia Salanti1.   

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. Copyright © 2012 John Wiley & Sons, Ltd.

Keywords:  2 × 2 contingency table; data extraction; meta-analysis; odds ratio

Year:  2012        PMID: 26053541     DOI: 10.1002/jrsm.1061

Source DB:  PubMed          Journal:  Res Synth Methods        ISSN: 1759-2879            Impact factor:   5.273


  2 in total

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Authors:  Majnu John; Todd Lencz; Anil K Malhotra; Christoph U Correll; Jian-Ping Zhang
Journal:  Meta Gene       Date:  2018-02-21

2.  Modeling of Recommendation System Based on Emotional Information and Collaborative Filtering.

Authors:  Tae-Yeun Kim; Hoon Ko; Sung-Hwan Kim; Ho-Da Kim
Journal:  Sensors (Basel)       Date:  2021-03-12       Impact factor: 3.576

  2 in total

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