Objectives: It is possible for baseline imbalances to occur between treatment groups for one or more variables in a randomized controlled trial, although the identification and detection of baseline imbalances remain controversial. If trials with baseline imbalances are combined in a meta-analysis, then this may result in misleading conclusions.
Study design and setting: The identification and consequences of baseline imbalances in meta-analyses are discussed. Metaregression using mean baseline scores as a covariate is proposed as a potential method for adjusting baseline imbalances within meta-analysis. We will use a recent systematic review looking at the effect of calcium supplements on weight as an illustrative case study.
Results: Meta-analysis conducted using the mean final values of the treatment groups as the outcome resulted in an apparent, statistically significant, treatment effect. However, using a meta-analysis of baseline values, this was shown to be due to the baseline imbalance between treatment groups, rather than as a result of any intervention received by the participants. Applying the method of metaregression demonstrated that there was in fact a smaller, statistically insignificant effect between treatment groups.
Conclusion: The meta-analyst should always consider the possibility of baseline imbalances and adjustments should be made wherever possible.