Meta-analyses involving cross-over trials: methodological issues

Abstract

We would like to make a correction to the description of the Becker–Balagtas method found in the 2002 International Journal of Epidemiology article by Elbourne et al.1 The article describes methods of combining parallel and cross-over trials for the purposes of meta-analysis. In the following summary, we will provide a revised description of the Becker–Balagtas approach with an example of how to implement it. The Becker–Balagtas approach is an estimation method used in the meta-analysis of cross-over trials with binary outcomes.1 It is considered a marginal method because it relies on the marginal probabilities of the outcome to estimate the odds ratio (OR).2 Typically, a conditional approach, such as the Mantel–Haenszel odds ratio (of the discordant pairs), is the usual effect estimate for cross-over trials.3 However, when summarizing results across study designs the Becker–Balagtas approach is the preferred method.3 To compute the Becker–Balagtas estimates, we first define the observed cell quantities from a cross-over trial. In the cross-over design, all subjects participate in all treatments in successive periods where the sequence of treatments is determined by randomization.1 For example, some subjects are randomized to receive placebo for the first period followed by the active treatment in the second period, others are randomized to receive the active treatment in the first period followed by the placebo in the second period. Each subject contributes two results for the active and placebo treatment periods.

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