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Correspondence

Modelling Methodologic Quality into Meta-Analyses and Pitfalls of Not Doing This

Division of Endocrinology, Department of Medicine, Mubarak Al-Kabeer Teaching Hospital, Kuwait University, P.O. Box 24923, Safat, 13110 Kuwait

(Email: sardoi@gmx.net).

The first 20% of the full text of this article appears below.

To the Editor:

In a meta-analysis of randomized trials comparing off-pump coronary artery bypass (OPCAB) with on-pump coronary artery bypass graft patency [1], the authors demonstrated in relative terms that the OPCAB approach significantly increased this risk, with the odds of graft occlusion being 51% higher (95% confidence limits, 15% to 99%) using a fixed effects model for data synthesis. It can be demonstrated (Figs 1A–1C) that if a random effects model [2] was used, the odds of graft occlusion increases to 65% higher, whereas with a quality effects model [3], this further increases to 80% higher. The studies depicted in the forest plots as follows are listed in order of weight within each meta-analysis (lowest to highest), and the analyses were run using MIX version 1.7 (Kitasato Clinical Research Center, Sagamihara, Japan) [4].

View larger version (9K):   Fig 1. Meta-analysis results by three methods: (A) Fixed effect results odds ratio (OR) of 1.51 (95% confidence interval [95% CI], 1.15 to 1.99); (B) quality effects results OR of 1.8 (95% CI, 1.25 to 2.58); and (C) random effects results OR of 1.65 (95% . . . [Full Text of this Article]

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