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A meta-analysis is a statistical method used to estimate an average, or common effect, over several studies. With therapeutic interventions (whether drug or non-drug) the meta-analysis is usually based on randomised controlled trials. In this reader’s guide we use the systematic review by Bravata et al1 of the effects of pedometers to increase physical activity to illustrate these concepts.
A good systematic review should have done a thorough search for all studies, appraised their quality, and selected the better studies for answering the question. We won’t go over the appraisal here but will focus on reading the combined results. Reading a meta-analyses can be broken down into 4 basic steps2:
1. What is the summary measure?
2. What does the Forest Plot show?
3. What does the pooled effect (average effect) mean?
4. Was it valid to combine studies?
1. WHAT IS A SUMMARY MEASURE?
First read the horizontal scale of the Forest plot to check which measure of effect has been used, and which side is “good” and “bad” for the treatment. The effect in each study can be summarised in different ways. For binary outcomes (2 × 2 table), the main options are relative risk (RR), odds ratios (OR), or risk differences (RD). For meta-analysis, usually relative measures (RR and OR) are preferred as they are more likely to remain similar from study to study (see the discussion on heterogeneity below). For continuous outcomes, the options are the difference in means or standardised means between the interventions tested. In the pedometer review, the outcome of interest is the mean difference in the number of steps (post-intervention steps per day − …
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