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What are systematic reviews?

Cochrane produces systematic reviews because they are the most reliable way to find out if a particular intervention or test is effective. 

When we do a systematic review, we carefully examine all of the scientific research in order to answer a particular question – for example, ‘Does treatment X help people with disease Y?’ – and then we work out what the overall effect is. We use sophisticated statistical methods to combine and compare several studies, sometimes hundreds, making our reviews more reliable than individual studies. 

Watch this video to learn more about systematic reviews, how researchers prepare them, and why they’re important for everyone who needs to make informed decisions about health. 

Video: What are systematic reviews? (3 mins 23s)

Video transcript

What are systematic reviews? Systematic reviews help make sense of many kinds of data. They're a way of reviewing all the data and results from research about a particular question in a standardized, systematic way. A systematic review helps to give an objective and transparent overview of all evidence surrounding a particular question.

The Cochrane logo visually represents how results from some systematic reviews can be explained. Here's how a systematic review works.

First, a question must be defined, and an objective method for asking the question is agreed. Imagine a circle as the area defined by a question. Everything inside it concerns the question. Everything outside it does not. In this circle, relevant data will be included.

A search for relevant data begins. This data can come from many sources, including data from clinical trials. Imagine the shapes represent datasets from different research, for example, different clinical trials.

The data set must be the right shape to fit: only data from research that matches certain criteria can be included, so that the results are reliable - for example, selecting research that is good quality and answers the defined question.

If the research meets the criteria, more detailed information about the research can be collected or extracted.

Information extracted can include: how the research was done (often called the method), who participated in the research (including how many people, how it was paid for - for example, funding sources), what happened (the outcomes).

This information is judged against the criteria in order to assess the quality of the research. Once the information is extracted, it can be combined using complex statistical methods to give an overall result from all of the data.

This circle is one way of representing this data visually. It's called a blobbogram or a forest plot.

The area of inquiry defined by the question be divided into a 'yes' and a 'no' half: a positive and a negative side. The shorter the line, the more confident we are of what the data is telling us.

Think of a longer line as less focused and scattered data and shorter as more focused and bunched. Imagine knowledge as light and ignorance as darkness: the more spread the focus of the light, the weaker it is and the less clear things are. If the light is focused and data is grouped more clearly, we can be more confident of what we see.

The diamond represents the combined results of all the data included. Because this combined result uses data from more sources than just one data set, it's considered more reliable and better evidence. The more data there is, the more confident we can be.