REVIEW ARTICLES

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SUMMARIZING RESEARCH FINDINGS: SYSTEMATIC REVIEW AND META-ANALYSIS

Effect size: refers to the size of a relationship between an expose and an outcome. The term is applied to measurement of the differences in the outcome between the study groups. Relative risk, odds ratio, and risk differences can be defined as effect sizes for dichotomous scale. Effect size of continuous variable is the standardized mean differences.

Fixed-effect model: a mathematical model that combines the results of studies that assume the effect of the intervention is constant in all subject population studied. Only within study variation is included when assessing the uncertainty of results.

Forest plot: a forest plot presents the means and variance for the difference for each pooled primary study. The line represents the standard error of the difference, the box represents the mean difference and its size proportional to the number of subjects in the study. The bottom entry in a forest plot is the summary estimate of the treatment difference and confidence interval for the summary difference (Figure 2).

Funnel plot: a graphical method of assessing bias; the effect size of each study is plotted against some measure of study information. If the shape of the plot resembles an inverted funnel, it can be stated that there is no evidence of publication bias within the systematic review (Figure 3).

Heterogeneity: the variability between studies in terms of key characteristics (i.e. ecological variables) quality (i.e. methodology) or effect (i.e. results). Statistical tests of heterogeneity may be used to assess whether the observed variability in effect size (i.e. study results) is greater than that expected to occur purely by chance.

Meta-regression: a multivariable model investigating effect size from individual studies, generally weighted by sample size, as a function of various study characteristics (i.e. to investigate whether study characteristics are influencing effect size).

Outlier : an outlier study in meta-analysis is study that results very different from the rest of the studies. Outlier could alter the conclusions of a meta-analysis.

Overall estimate: is the pooled estimate from a meta-analysis. The overall estimate from a meta-analysis is always displayed with its confidence interval.

Primary studies: Individual studies contributing to a systematic review are called primary studies whereas a systematic review is a form of a secondary study.

Publication bias: publication bias refers to the problem that positive results are more likely to be published than negative results and this may therefore give a misleading assessment of the impact of an intervention. Publication bias can be examined via a funnel plot.

Random-effects model:  a mathematical model for combining the results of studies that allow for variation in the effect of the intervention amongst the subject populations studied. Both within-study variation and between-study variation is included when assessing the uncertainty of results.

Review: article that summarizes a number of primary studies and discusses the effectiveness of a particular intervention. It may not be a systematic review.

Search strategy: description of the methodology used to locate and identify research articles pertinent to a systematic review, as specified within the relevant protocol. It includes a list of search terms, based on the subject, intervention and outcome of the review, to be used when searching electronic databases, websites, reference lists and when engaging with personal contacts. If required, the strategy may be modified once the search has commenced. 

Sensitivity analysis: repetition of the analysis using different sets of assumptions in order to determine the impact of variation arising from these assumptions, or uncertain decisions, on the results of a systematic review.

Subgroup analysis: used to determine if the effects of an intervention vary between subgroups in the systematic review.

Weighted mean difference: a method used to combined measures on continuous scales (where the mean, standard deviation and sample size in each group are known) and the weight given to each study is determined by the precision of its estimate of effect.

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