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Draw where each network estimate's evidence comes from, study by study

Source: R/cinema_contribution.R
cinema_contribution.Rd

Draws the contribution of every study to every estimate of a network meta-analysis, from netmeta::netcontrib(x, study = TRUE): one bar per comparison, split into studies as wide as their share of the estimate and colored by each study's risk of bias or indirectness, with the studies grouped low, moderate and high as CINeMA draws them; a comparison by study matrix of the same numbers, whose squares mark with an outline the studies that compare that pair head to head; and a small network.

Usage

cinema_contribution(
  x,
  ...,
  color = NULL,
  positions = NULL,
  title = NULL,
  caption = NULL,
  family = "Lato"
)

Arguments

x

Judgments from cinema_judge() made with study judgments, or a network meta-analysis from netmeta::netmeta(), judged with the arguments in ....

...

When x is a netmeta fit, arguments for cinema_judge(): the study judgments rob and indirectness, at least one of them, and optionally contributions, small_values, order and pooled.

color

Which judgment colors the studies at first, "rob" or "indirectness". Defaults to risk of bias when it was given.

positions

Optional data frame placing the treatments of the small network by hand, with columns treatment, x and y and y pointing up, as in ggnma(). Defaults to a circle.

title, caption

Title above the plot and note below it. A caption you give is added above the default notes.

family

Font family. The package ships Lato and registers it on load.

Value

An object of class cinema_contribution, which prints as an interactive widget. Use graph_widget(), graph_plot() or graph_save() for the widget, a static ggplot or a file. The field contributions holds the share of each estimate from each study.

Details

In the widget, a switch colors the studies by risk of bias or by indirectness. Selecting a comparison, from its label, the matrix or the menu, lights its bar and matrix row and widens each line of the small network by the share of the estimate that flows through it. Selecting a study, from the matrix, its button or the panel, dims the others and marks the comparisons it randomized. Clicking a part of a bar lists the studies with that judgment in that estimate, with their shares and the reasons for their judgments. The labels and matrix headers can be reached with the keyboard, and a sentence under the controls says what the selection shows.

Contributions say where an estimate's information comes from, not how trustworthy it is. Dropping a study would change the whole fit, so there is deliberately no switch that removes one and rescales the bars.

Sources

Nikolakopoulou A, Higgins JPT, Papakonstantinou T, et al. CINeMA: an approach for assessing confidence in the results of a network meta-analysis. PLoS Medicine 2020;17(4):e1003082. doi:10.1371/journal.pmed.1003082

Papakonstantinou T, Nikolakopoulou A, Higgins JPT, Egger M, Salanti G. CINeMA: software for semiautomated assessment of the confidence in the results of network meta-analysis. Campbell Systematic Reviews 2020;16:e1080. doi:10.1002/cl2.1080

Papakonstantinou T, Nikolakopoulou A, Rucker G, et al. Estimating the contribution of studies in network meta-analysis: paths, flows and streams. F1000Research 2018;7:610.

Examples

# \donttest{
if (requireNamespace("netmeta", quietly = TRUE) &&
    requireNamespace("meta", quietly = TRUE)) {
  pw <- meta::pairwise(treat = treatment, event = pasi75_r,
                       n = pasi75_n, studlab = study,
                       data = psoriasis_nma, sm = "OR")
  nma <- netmeta::netmeta(pw, common = FALSE)
  # Illustrative judgments, invented for this example.
  rob <- data.frame(
    study = c("CLEAR", "ERASURE", "FEATURE", "FIXTURE", "JUNCTURE"),
    judgment = c("high", "low", "some concerns", "low", "some concerns")
  )
  cinema_contribution(nma, rob = rob, small_values = "undesirable",
                      caption = "Illustrative judgments, not published assessments.")
}
# }