It’s not that the other studies don’t matter – we’ll come back to that later. And one trial – the HF-ACTION trial – accounts for just over 70% of the result. This forest plot shows you the weight each of 6 studies is contributing to the result (the line in bold – click to see a bigger version). It arrives at a weighted average, taking into account size of the study, for example. I’ve written a quick primer on understanding these here.Įach meta-analysis doesn’t just add studies up. Some background first: the figure below is a forest plot of a single meta-analysis from within a systematic review. Understanding and discussing that dominant study is critical. A study by Paul Glasziou and colleagues in 2010 found that even when there were several trials, the most precise one carried on average half the weight of the results – and around 80% of the time the conclusion of the meta-analysis was pretty much the same as that single study. Secondly, it’s not at all unusual for a meta-analysis to be heavily dominated by a single study. A bad or patchy meta-analysis might not come to as reliable conclusions as a well-conducted, adequately powered single study. There are subjective judgments every step of the way, giving small teams of like-minded people plenty of room to steer in a desired direction if they want to. It’s a non-experimental or descriptive study. A single study becomes a puny thing, to be ignored even.īut while combined results can carry a lot of weight, there are 3 main problems with the idea that a meta-analysis always trumps a single study.įirstly, a systematic review and meta-analysis isn’t a formal experimental study. It’s a heavy-duty effort, and it’s often described as the ultimate study, outweighing all others. A meta-analysis is a safer starting point than a single study – but it won’t necessarily be more reliable.Ī meta-analysis is usually part of a systematic review. This time, I’m pointing to some common traps.ġ. In last year’s post, I explained the basics, and concentrated on some ways to see the value of a meta-analysis. Using a variety of statistical methods, some of which were purpose-built, you can condense a vast amount of information into a single summary statistic. Meta-analysis is combining and analyzing data from more than one study at a time. With meta-analyses booming, including many that are poorly done or misinterpreted, it’s definitely time for a sequel! Last year I wrote a post of “5 Key Things to Know About Meta-Analysis”. It was a great way to focus – but it was hard keeping to only 5.
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