Forest plot of juxtaposing several network meta-analysis models

Provides a forest plot with the posterior median and 95% credible and prediction intervals for comparisons with the selected intervention (comparator) in the network under several network meta-analyses models, as well as a forest plot with the corresponding SUCRA values.

Usage

forestplot_juxtapose(
  results,
  compar,
  name,
  drug_names,
  axis_title_size = 12,
  axis_text_size = 12,
  caption_text_size = 9,
  label_size = 3.5,
  position_width = 0.8
)

Arguments

results: A list of at least two objects of S3 class run_model or run_metareg. See 'Value' in run_model and run_metareg.
compar: A character to indicate the comparator intervention. It must be any name found in drug_names.
name: A vector of characters referring to the juxtaposed models. If the argument is left unspecified, the names of models appear as 'Model X' with 'X' being the order/position of each model in the argument results.
drug_names: A vector of labels with the name of the interventions in the order they appear in the argument data of run_model. If drug_names is not defined, the order of the interventions as they appear in data is used, instead.
axis_title_size: A positive integer for the font size of x axis title. axis_title_size determines the axis.title argument found in the theme's properties in the R-package ggplot2.
axis_text_size: A positive integer for the font size of axis text (both axes). axis_text_size determines the axis.text argument found in the theme's properties in the R-package ggplot2.
caption_text_size: A positive integer for the font size of caption text. caption_text_size determines the plot.caption argument found in the theme's properties in the R-package ggplot2.
label_size: A positive integer for the font size of labels appearing on each interval. label_size determines the size argument found in the geom's aesthetic properties in the R-package ggplot2.
position_width: A positive integer specifying the vertical position of the intervals. position_width is found in the geom's aesthetic properties in the R-package ggplot2.

Value

A list of the following two figures:

forest_plots: A panel of two forest plots: (1) a forest plot on the posterior median and 95% credible and prediction intervals for comparisons with the selected comparator treatment (specified with compar), and (2) a forest plot on the posterior mean and 95% credible interval of SUCRA values of the treatments (Salanti et al., 2011).
tau_plot: A forest plot on the posterior median and 95% credible interval of the between-study standard deviation.

Details

The y-axis of the forest plot on forest_plots displays the labels of the treatments in the network; the selected treatment that comprises the compar argument is annotated in the plot with the label 'Comparator intervention'. For each comparison with the selected treatment, the 95% credible and prediction intervals are displayed as overlapping lines. Black lines refer to estimation under both analyses. Coloured lines refer to prediction under each model, respectively. The corresponding numerical results are displayed above each line: 95% credible intervals are found in parentheses, and 95% predictive intervals are found in brackets. Odds ratios, relative risks, and ratio of means are reported in the original scale after exponentiation of the logarithmic scale.

If one of the models refer to network meta-regression (run_metareg) the results on treatment effects (estimation and prediction) and SUCRA values refer to the covariate value selected when employing run_metareg.

The y-axis for the forest plot on SUCRA values displays the labels of the treatments in the network. The corresponding numerical results are displayed above each line.

In forest_plots and tau_plot, the treatments are sorted in the descending order of their SUCRA values based on the first model specified in results.

Important note: forestplot_juxtapose should be used to compare the results from several network meta-analysis models that contain the same treatments, have the same meta-analysis model (fixed-effect or random-effects) and the same effect measure; otherwise the execution of the function will be stopped and an error message will be printed on the R console.

forestplot_juxtapose is used only for a network of treatments. In the case of two treatments, the execution of the function will be stopped and an error message will be printed on the R console.

References

Salanti G, Ades AE, Ioannidis JP. Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol 2011;64(2):163–71. doi:10.1016/j.jclinepi.2010.03.016

Author

Loukia M. Spineli