Understanding systematic reviews: the meta-analysis graph (also called 'forest plot')

Emergent methods for inactivation of Cronobacter sakazakii in foods: A systematic review and meta-analysis

Cronobacter sakazakii is a potentially pathogenic bacterium that is resistant to osmotic stress and low aw, and capable of persisting in a desiccated state in powdered infant milks. It is widespread in the environment and present in various products. Despite the low incidence of cases, its high mortality rates of 40 to 80 % amongst neonates make it a microorganism of public health interest. This current study performed a comparative assessment between current reduction methods applied for C. sakazakii in various food matrices, indicating tendencies and relevant parameters for process optimization. A systematic review and meta-analysis were conducted, qualitatively identifying the main methods of inactivation and control, and quantitatively evaluating the effect of treatment factors on the reduction response. Hierarchical clustering dendrograms led to conclusions on the efficiency of each treatment. Review of recent research trend identified a focus on the potential use of alternative treatments, with most studies related to non-thermal methods and dairy products. Using random-effects meta-analysis, a summary effect-size of 4-log was estimated; however, thermal methods and treatments on dairy matrices displayed wider dispersions - of τ2 = 8.1, compared with τ2 = 4.5 for vegetal matrices and τ2 = 4.0 for biofilms. Meta-analytical models indicated that factors such as chemical concentration, energy applied, and treatment time had a more significant impact on reduction than the increase in temperature. Non-thermal treatments, synergically associated with heat, and treatments on dairy matrices were found to be the most efficient.

Long-term impact of sewage sludge application on soil microbial biomass: An evaluation using meta-analysis

The Long-Term Sludge Experiments (LTSE) began in 1994 as part of continuing research into the effects of sludge-borne heavy metals on soil fertility. The long-term effects of Zn, Cu, and Cd on soil microbial biomass carbon (C_mic) were monitored for 8 years (1997-2005) in sludge amended soils at nine UK field sites. To assess the statutory limits set by the UK Sludge (Use in Agriculture) Regulations the experimental data has been reviewed using the statistical methods of meta-analysis. Previous LTSE studies have focused predominantly on statistical significance rather than effect size, whereas meta-analysis focuses on the magnitude and direction of an effect, i.e. the practical significance, rather than its statistical significance. The results presented here show that significant decreases in C_mic have occurred in soils where the total concentrations of Zn and Cu fall below the current UK statutory limits. For soils receiving sewage sludge predominantly contaminated with Zn, decreases of approximately 7-11% were observed at concentrations below the UK statutory limit. The effect of Zn appeared to increase over time, with increasingly greater decreases in C_mic observed over a period of 8 years. This may be due to an interactive effect between Zn and confounding Cu contamination which has augmented the bioavailability of these metals over time. Similar decreases (7-12%) in C_mic were observed in soils receiving sewage sludge predominantly contaminated with Cu; however, C_mic appeared to show signs of recovery after a period of 6 years. Application of sewage sludge predominantly contaminated with Cd appeared to have no effect on C_mic at concentrations below the current UK statutory limit.

Graphical displays for meta-analysis: An overview with suggestions for practice

Meta-analyses are fundamental tools for collating and synthesizing large amounts of information, and graphical displays have become the principal tool for presenting the results of multiple studies of the same research question. We review standard and proposed graphical displays for presentation of meta-analytic data, and offer our recommendations on how they might be presented to provide the most useful and user-friendly illustrations. We concentrate on graphs that specifically aim to present similar sorts of univariate results from multiple studies. We start with forest plots and funnel plots, and proceed to Galbraith (or radial) plots, L'Abbé (and related) plots, further plots useful for investigating heterogeneity, plots useful for model diagnostics and plots for illustrating likelihoods and Bayesian meta-analyses. Copyright © 2010 John Wiley & Sons, Ltd.

More than numbers: the power of graphs in meta-analysis

In meta-analysis, the assessment of graphs is widely used in an attempt to identify or rule out heterogeneity and publication bias. A variety of graphs are available for this purpose. To date, however, there has been no comparative evaluation of the performance of these graphs. With the objective of assessing the reproducibility and validity of graph ratings, the authors simulated 100 meta-analyses from 4 scenarios that covered situations with and without heterogeneity and publication bias. From each meta-analysis, the authors produced 11 types of graphs (box plot, weighted box plot, standardized residual histogram, normal quantile plot, forest plot, 3 kinds of funnel plots, trim-and-fill plot, Galbraith plot, and L'Abbé plot), and 3 reviewers assessed the resulting 1,100 plots. The intraclass correlation coefficients (ICCs) for reproducibility of the graph ratings ranged from poor (ICC = 0.34) to high (ICC = 0.91). Ratings of the forest plot and the standardized residual histogram were best associated with parameter heterogeneity. Association between graph ratings and publication bias (censorship of studies) was poor. Meta-analysts should be selective in the graphs they choose for the exploration of their data.