Summarising, synthesis and meta-analysis

Summarising, synthesis and meta-analysis

It is essential is that you summarise and synthesise the results to reflect on what the review is telling you, and in particular how it is answering the question you set at the beginning.

Synthesis is very nicely summarised in “Summarizing study characteristics and preparing for synthesis” – from the Cochrane Handbook https://training.cochrane.org/handbook/current/chapter-09

Key Points:

• Synthesis is a process of bringing together data from a set of included studies with the aim of drawing conclusions about a body of evidence. This will include synthesis of study characteristics and, potentially, statistical synthesis of study findings.

• A general framework for synthesis can be used to guide the process of planning the comparisons, preparing for synthesis, undertaking the synthesis, and interpreting and describing the results.

• Tabulation of study characteristics aids the examination and comparison of PICO elements across studies, facilitates synthesis of these characteristics and grouping of studies for statistical synthesis.

Before you even think of the possibility of a meta-analysis, you need to summarise your findings. Here are some steps you might take:

Be clear about the questions that the literature review seeks to answer

• And in doing so be very specific about the terms used and also specify outcomes/end points of interest (as in the PICO statement).

• Then define what outcomes on which you wish to gain information.

• Once you have done your search and found the relevant studies read them all, assessed their quality and put them in the studies table.

• You will then know how many studies were eligible and how many studied were relevant to your questions.

• Then start grouping the studies accordingly to your questions and start looking at the outcomes – again how many studied which outcomes, the type of studies and form a qualitative impression/assessment of the evidence gathered.

• You can also look at the data – in terms of ‘effect size’ [Note: "Effect size is a simple way of quantifying the difference between two groups that has many advantages over the use of tests of statistical significance alone. Effect size emphasises the size of the difference rather than confounding this with sample size". See: What is effect size and why it is important].
  

• You are then ready to create a synthesis of what you have learned and how it relates to the question(s) you asked at the start of the review.

• After that it becomes more specialised – in terms of pooling data- but you should know which data are worth pooling and which not - and if you were able to do fuller meta-analysis then how could it be done. In a few instances, such as where you have summarised a number of randomised controlled trials, you may want to perform a meta-analysis, but this will not be possible for most reviews.

What is meta-analysis?

“Meta-analysis is a research process used to systematically synthesise or merge the findings of single, independent studies, using statistical methods to calculate an overall or ‘absolute’ effect. Meta-analysis does not simply pool data from smaller studies to achieve a larger sample size. Analysts use well recognised, systematic methods to account for differences in sample size, variability (heterogeneity) in study approach and findings (treatment effects) and test how sensitive their results are to their own systematic review protocol (study selection and statistical analysis). https://ebn.bmj.com/content/16/1/3”.

It is a complex process, nicely set out below from Crombie et al, and in the attached file:

• Meta-analysis is a statistical technique for combining the findings from independent studies.
• Meta-analysis is most often used to assess the clinical effectiveness of healthcare interventions; it does this by combining data from two or more randomised control trials.
• Meta-analysis of trials provides a precise estimate of treatment effect, giving due weight to the size of the different studies included.
• The validity of the meta-analysis depends on the quality of the systematic review on which it is based.
• Good meta-analyses aim for complete coverage of all relevant studies, look for the presence of heterogeneity, and explore the robustness of the main findings using sensitivity analysis.

Should you want to perform a meta-analysis, there are a number of software options, including RevMan from the Cochrane Collaboration.