Good, we've made it to the end.
We're going discuss two very exciting topics close to my heart,
the meta-analysis and the systematic review.
Let's start with meta-analysis.
Meta-analysis, an analysis of analysis.
So we're really going to combine previous literature,
previous results into one study.
And we really hope that we can get more powerful results that way,
that our results are more generalizable.
Let's look at an example.
Now Geng and colleagues, they looked the use of single incision versus the standard
laparoscopic cholecystectomy.
Now a standard laparoscopic cholecystectomy is really the standard of
care, but we are now wondering is a single incision actually better?
Are you going to get better operative times?
Are you going to get better pain relief?
Are you going to have better cosmetic outcomes?
We're not sure.
So there are many randomized controlled trials
in looking at these two procedures but they have various outcomes.
We're not sure which one is best.
There's even been previous meta-analysis and they couldn't come up with the odds.
So that this was a large meta-analysis including a lot of randomized
controlled trials to see if we can pinpoint the difference between these two.
So let's look at the method section.
What was the steps they went through to make this a meta-analysis.
First of all the literature search.
You really have to search as wide as possible.
You cannot leave out an important trial,
a trial which would have changed the outcome of your analysis.
You really have to be all inclusive, look everywhere for published literature.
Then you have to be very specific about your inclusion and exclusion criteria for
all these papers that were found that could be included in the meta-analysis.
You really have got to be clear about those.
Why was that certain papers excluded, and why were certain papers actually included?
Then there's the matter of the quality of the papers.
How do you go about deciding what the quality of a paper is,
really can be very subjective.
Fortunately though, there are some scoring systems that can help out.
And then we've got to do the data assessment.
We've got to take the data in those trials and
we've got to bring them into our own analysis.
And we've got to be careful there.
We can't always compare the data.
Say, for instance, there's a certain laboratory test and
there's more than one way to do it, there's more than one piece of apparatus
that the laboratory can use and they're known to have slightly different results.
You've got to be careful what you are comparing or
what you are including In your final analysis.
A quick word about the systematic reviews.
This has really become the definitive word in research.
What we do there, we combine quantitative analysis with a qualitative analysis.
In other words, many of them, almost all of them these days,
will include a meta-analysis as well, but we will also get a lot of expert opinion,
a lot of description into those studies.
It really is a wonderful piece of literature.
If you're a resident student, a registrar, and
you want to learn something about a topic, want to get to speed on a topic,
a systematic review is really the place to go.
You're going to get a summary of all the literature that's gone before,
an analysis of that, and qualitative discussion on that analysis.
And the results of a systematic review really should be an exhaustive
resource for you to go and get information on a specific topic.
Now fortunately these days they have become standardized.
On the screen you will see the website of the PRISMA guidelines.
It's really a set checklist of guidelines to go through
to work through when you develop meta-analysis and systematic reviews so
we can have some form of standard out there in the literature.
So that is one way of looking at all the different study designs.
I hope you have a much better understanding of it now.
Go out, read some papers, and form your own opinion as to
how the study was designed, what type of study design it was.
In the next set of lectures, we're going to look at data types.
See you then.