Clinical Trials

Clinical Trials: A Practical Guide ■❚❙❘There will only be a substantial difference in the pooled treatment effectcomputed by the two methods if there is considerable heterogeneity between thecomponent studies. Whether the fixed- or random-effects model should be usedfor a specific meta-analysis depends on the presence of statistically significantheterogeneity (evaluated by formal heterogeneity testing). The random-effectsmodel is usually recommended when statistically significant heterogeneity ispresent between study results. More importantly, the source of heterogeneityshould be investigated to identify the types of clinical heterogeneity in terms of, eg,patient selection, baseline disease severity, dose schedules, and years of follow-up,that might explain all or part of the statistical heterogeneity [10]. In the absenceof statistically significant heterogeneity, the fixed-effects model is advocated [4].What key objectives are there when results are presented?In any meta-analysis it is important that the account of the analysis is transparentand that the reasons for including and excluding various studies and other data aredocumented. Both the sources and the search strategy for this evidence need to bedescribed and the criteria used to assess the quality of the included studies shouldbe detailed. By doing this, any bias inadvertently caused by the researcher due tohis/her method of study selection is transparent and the reader can appreciate thelimitations of the evidence base, the efforts made to address these limitations, andhow robust the inferences drawn from the results are. The results of a meta-analysiscan be best presented in a graph like Figure 2.What are the main concerns about meta-analysis?Meta-analysis is a useful way of combining available evidence. The most commoncriticism is that the pooled estimate is not a meaningful measure and it is notapplicable to ‘real life’ medical practice for a number of reasons [4]. These reasonsinclude differences between studies, poor quality of some or all of the studiesincluded, and a selection bias towards published studies. Essentially, the criticismsare that when the data come from several separate studies, adjustments might notaccount for the differences between the studies.The second problem, right from the outset, is that in a meta-analysis it isimpossible to know which studies are missing because they were never captured,even at the stage of screening for generally relevant studies. An inexpert search ofthe literature might not identify all relevant studies [4,6].449