ceef.plot.bcea {BCEA} R Documentation

## Cost-Effectiveness Efficiency Frontier (CEEF) Plot

### Description

The line connecting successive points on a cost-effectiveness plane which each represent the effect and cost associated with different treatment alternatives. The gradient of a line segment represents the ICER of the treatment comparison between the two alternatives represented by that segment. The cost-effectiveness frontier consists of the set of points corresponding to treatment alternatives that are considered to be cost-effective at different values of the cost-effectiveness threshold. The steeper the gradient between successive points on the frontier, the higher is the ICER between these treatment alternatives and the more expensive alternative would be considered cost-effective only when a high value of the cost-effectiveness threshold is assumed. Points not lying on the cost-effectiveness frontier represent treatment alternatives that are not considered cost-effective at any value of the cost-effectiveness threshold.

### Usage

## S3 method for class 'bcea'
ceef.plot(
he,
comparators = NULL,
pos = c(1, 1),
start.from.origins = TRUE,
threshold = NULL,
flip = FALSE,
dominance = TRUE,
relative = FALSE,
print.summary = TRUE,
graph = c("base", "ggplot2"),
print.plot = TRUE,
...
)

ceef.plot(he, ...)


### Arguments

 he A bcea object containing the results of the Bayesian modelling and the economic evaluation. comparators Vector specifying the comparators to be included in the frontier analysis. It must have a length > 1. Default as NULL includes all the available comparators. pos Parameter to set the position of the legend (only relevant for multiple interventions, ie more than 2 interventions being compared). Can be given in form of a string (bottom|top)(right|left) for base graphics and bottom|top|left|right for ggplot2. It can be a two-elements vector, which specifies the relative position on the x and y axis respectively, or alternatively it can be in form of a logical variable, with FALSE indicating to use the default position and TRUE to place it on the bottom of the plot. start.from.origins Logical. Should the frontier start from the origins of the axes? The argument is reset to FALSE if the average effectiveness and/or costs of at least one comparator are negative. threshold Specifies if the efficiency should be defined based on a willingness-to-pay threshold value. If set to NULL (the default), no conditions are included on the slope increase. If a positive value is passed as argument, to be efficient an intervention also requires to have an ICER for the comparison versus the last efficient strategy not greater than the specified threshold value. A negative value will be ignored with a warning. flip Logical. Should the axes of the plane be inverted? dominance Logical. Should the dominance regions be included in the plot? relative Logical. Should the plot display the absolute measures (the default as FALSE) or the differential outcomes versus the reference comparator? print.summary Logical. Should the efficiency frontier summary be printed along with the graph? See Details for additional information. graph A string used to select the graphical engine to use for plotting. Should (partial-)match the two options "base" or "ggplot2". Default value is "base". print.plot Logical. Should the efficiency frontier be plotted? ... If graph_type="ggplot2" and a named theme object is supplied, it will be added to the ggplot object. Ignored if graph_type="base". Setting the optional argument include.ICER to TRUE will print the ICERs in the summary tables, if produced.

### Details

Back compatibility with BCEA previous versions: The bcea objects did not include the generating e and c matrices in BCEA versions <2.1-0. This function is not compatible with objects created with previous versions. The matrices can be appended to bcea objects obtained using previous versions, making sure that the class of the object remains unaltered.

The argument print.summary allows for printing a brief summary of the efficiency frontier, with default to TRUE. Two tables are plotted, one for the interventions included in the frontier and one for the dominated interventions. The average costs and clinical benefits are included for each intervention. The frontier table includes the slope for the increase in the frontier and the non-frontier table displays the dominance type of each dominated intervention. Please note that the slopes are defined as the increment in the costs for a unit increment in the benefits even if flip = TRUE for consistency with the ICER definition. The angle of increase is in radians and depends on the definition of the axes, i.e. on the value given to the flip argument.

If the argument relative is set to TRUE, the graph will not display the absolute measures of costs and benefits. Instead the axes will represent differential costs and benefits compared to the reference intervention (indexed by ref in the bcea() function).

### Value

 ceplane A ggplot object containing the plot. Returned only if graph_type="ggplot2".

The function produces a plot of the cost-effectiveness efficiency frontier. The dots show the simulated values for the intervention-specific distributions of the effectiveness and costs. The circles indicate the average of each bivariate distribution, with the numbers referring to each included intervention. The numbers inside the circles are black if the intervention is included in the frontier and grey otherwise. If the option dominance is set to TRUE, the dominance regions are plotted, indicating the areas of dominance. Interventions in the areas between the dominance region and the frontier are in a situation of extended dominance.

### Author(s)

Andrea Berardi, Gianluca Baio

### References

Baio G (2013). Bayesian Methods in Health Economics. CRC.

IQWIG (2009). “General Methods for the Assessment of the Relation of Benefits to Cost, Version 1.0.” Institute for Quality and Efficiency in Health Care (IQWIG).

bcea()

### Examples


## create the bcea object m for the smoking cessation example
data(Smoking)
m <- bcea(eff, cost, ref = 4, Kmax = 500, interventions = treats)

## produce plot
ceef.plot(m, graph = "base")

## tweak the options
## flip axis
ceef.plot(m,
flip = TRUE,
dominance = FALSE,
start.from.origins = FALSE,
print.summary = FALSE,
graph = "base")