Is a statistical technique that is used to combine the results of several studies?
The UK Faculty of Public Health has recently taken ownership of the Health Knowledge resource. This new, advert-free website is still under development and there may be some issues accessing content. Additionally, the content has not been audited or verified by the Faculty of Public Health as part of an ongoing quality assurance process and as such certain material included maybe out of date. If you have any concerns regarding content you should seek to independently verify this. Show
PLEASE NOTE: We are currently in the process of updating this chapter and we appreciate your patience whilst this is being completed. A systematic review draws together the results of several primary research studies. They are used when there is an important clinical question, but many clinical studies, perhaps with conflicting results. A systematic review seeks to provide an overview of the findings of the individual studies, highlighting possible answers, as well as any remaining gaps in knowledge. The Cochrane Collaboration defines a systematic review as 'a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant research and to collect and analyse data from studies that are included in the review.'1 Systematic reviews synthesise the results of multiple primary
investigations by using strategies that limit bias and random error. These include a comprehensive search of all potentially relevant articles.2 In the past, literature reviews were not as rigorous, and were often compiled by experts writing with a particular point of view, making dispassionate analysis difficult to achieve. It is thought, for example, that if original studies of the effects of anti-platelet therapies after myocardial infarction had been systematically reviewed, the
benefits of therapy would have been apparent as early as the mid-1970s.3 The systematic review process There is an established process recommended to minimise bias when selecting articles for review. Explicit, reproducible search strategies and eligibility criteria are used and every effort should be made to search a variety of sources for relevant articles, including grey and unpublished literature. Davies and Crombie outline the steps in this process:3
Data sources for a systematic review2 Greenhalgh provides a checklist of possible data sources that could be searched to provide articles to include in a systematic review.4 All of these should ideally be used and, if they have not been, the authors of the review should explain why.
Strengths of a systematic review
Limitations of systematic reviews
Meta-analysis A meta-analysis is a statistical technique used to combine and summarise the results of several independent studies that addressed the same hypothesis or clinical question in the same way. As well as synthesising the numerical data to provide a single estimate of effect, the meta-analysis should tabulate relevant information on the inclusion criteria, sample size, baseline patient characteristics, withdrawal rate, and results of primary and secondary end points of all the studies included.2 Meta-analyses are commonly used to assess the clinical effectiveness of health interventions from two or more randomised controlled trials. They are viewed as providing a more effective and accurate method of estimating a treatment effect, drawing on data from all the studies included. In a meta-analysis the overall effect of an intervention is calculated using weighted averages of the results from multiple trials. The weighting given to individual studies is based on the inverse variance of the effect size, which itself is largely a function of the sample size. So larger studies tend to result in a smaller variance, and thus contribute more to the final meta-analysis than smaller studies with a larger variance. There are two broad types of meta-analysis models used: fixed effects and random effects. Fixed effects meta-analyses are used when each of the included studies is thought to be clinically and methodologically similar (i.e. they are relatively homogenous and are thus each measuring the same – or fixed – effect). Random-effects meta-analyses are used where there is heterogeneity between included studies, and these are more conservative – giving wider confidence intervals for the final pooled estimate and larger p values. The results of a meta-analysis are plotted on a forest plot. These show the effect estimates (such as an odds ratio or relative risk) from each individual study as a shaded square, where the size of the square is proportional to its weighting, along with its confidence interval. The pooled estimate is given at the bottom as a diamond, where the middle of the diamond represents the pooled effect size and the edges delineate the pooled confidence interval. An example of a forest plot is shown below.(Reproduced from 5) Insert Forest Plot diagram here: Meta-analyses are used increasingly to establish clinical policy. The validity of the meta-analysis depends on both the quality of the original studies and the methods of systematic review used to identify them. The statistical methods used to assess heterogeneity and publication bias are addressed in the Section 1B chapter “Comparison of survival rates, heterogeneity, funnel plots, the role of Bayes theorem”. Strengths of a meta-analysis
Limitations of a meta-analysis
References
© Helen Barratt, Maria Kirwan 2009, Saran Shantikumar 2018 Is a statistical technique for combining the results of several studies to reach an overall conclusion?A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analyses can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error.
What is a method that allows researchers to combine the results of several studies on a similar topic in order to establish the strength of an effect?Meta-analysis is a well-known approach for obtaining a common intervention effect from several similar trials. The heterogeneity among the individual studies' estimates of effects, the within-study variance of the outcome measure(s), and a quality assessment of the studies are determined.
What type of research design combines the results of many studies?Meta-analysis is the statistical combination of results from two or more separate studies. Potential advantages of meta-analyses include an improvement in precision, the ability to answer questions not posed by individual studies, and the opportunity to settle controversies arising from conflicting claims.
Which of the following allows researchers to combine the statistical results of many studies to arrive at an overall conclusion?Meta-analyses are statistical techniques for combining the findings from independent studies and can be used in these cases to determine an overall estimate of the effect or rate of interest.
|