The second, third, and fourth modules have helped you learn how to read articles about diagnosis, therapy, and prognosis respectively. Now, it's time to learn about how to read an article about meta-analysis. While on the surface more complex and involved than most studies, by applying the principles learned in the first few modules you'll soon be comfortable reading and interpreting these studies.
One area of confusion is the distinction between review articles, systematic reviews, and meta-analyses. The diagram below illustrates their relationship using a Venn diagram:
Review articles (also called overviews) are the broadest category. Most review articles are unsystematic, because the author does not look at all of the evidence. A systematic review has a formal approach to gathering, evaluating, and presenting the evidence. Some systematic reviews are meta-analyses; a meta-analysis goes the final step by using formal statistical methods to calculate a summary result or results.
There are two major reasons to do a meta-analysis:
- To quantitatively combine the results of previous studies to arrive at a summary estimate
- As a "study of studies", to help guide further research and identify reasons for heterogeneity between studies
Meta-analyses of the first kind can help resolve medical controversies caused by conflicting studies, are an inexpensive alternative to very large randomized trials, and can in this way shape health policy. The second kind of meta-analysis is particularly useful for designing future studies, by systematically identifying key patient and study characteristics from previous work.
Meta-analyses were initially used in the social sciences in the mid-1970's, and were adapted to medical data sets in the early to mid-1980's. The number of meta-analyses is growing rapidly, based on the results of this Medline search for the keyword "meta-analysis":
|
Years |
Number of meta-analyses in Annals, JAMA, Lancet, NEJM |
|
1971-75 |
0 |
|
1976-80 |
0 |
|
1981-85 |
1 |
|
1986-90 |
32 |
|
1991-95 |
175 |
Meta-analyses often form the initial step of a cost-effectiveness analysis, decision analysis, or grant application. Once you've done all of that background work, why not publish it?!?! While the results usually correspond to later randomized trials, they do not always (LeLorier, 1997):
|
Results of RCT |
||
|
Results of meta-analysis |
Positive |
Negative |
|
Positive |
13 |
6 |
|
Negative |
7 |
14 |
In the next section, you will learn the steps in a good meta-analysis. Understanding these steps is important, even if you never plan to do one yourself, because it helps you understand how to critically appraise this type of study.