BMJ  2007;335:914-916 (3 November), doi:10.1136/bmj.39343.408449.80

Analysis

Uncertainty in heterogeneity estimates in meta-analyses

Clinical Trials and Evidence-Based Medicine Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece

John Ioannidis, Nikolaos Patsopoulos, and Evangelos Evangelou argue that, although meta-analyses often measure heterogeneity between studies, these estimates can have large uncertainty, which must be taken into account when interpreting evidence

The first 150 words of the full text of this article appear below.

Summary points The extent of between study heterogeneity should be measured when interpreting results of meta-analyses Meta-analyses rarely document uncertainty in estimates of heterogeneity Our evaluation of a large number of meta-analyses shows a wide range of uncertainty about the extent of heterogeneity in most Confidence intervals of I2 should be calculated and considered when interpreting meta-analyses

An important aim of systematic reviews and meta-analyses is to assess the extent to which different studies give similar or dissimilar results.¹ Clinical, methodological, and biological heterogeneity are often topic specific, but statistical heterogeneity can be examined with the same methods in all meta-analyses. Therefore, the perception of statistical heterogeneity or homogeneity often influences meta-analysts and clinicians in important decisions. These decisions include whether the data are similar enough to combine different studies; whether a treatment is applicable to all or should be "individualised" because of variable benefits or harms in different types of patients; . . . [Full text of this article]

Evaluating heterogeneity between studies

Interpreting heterogeneity in selected meta-analyses

Uncertainty in I²: large scale survey of meta-analyses

Technical aspects

Concluding comments

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