plot_clinical_impact: Plot the clinical impact curve from a DecisionCurve object.
In DecisionCurve: Calculate and Plot Decision Curves

For a given population size, plot the number of subjects classified as high risk, and the number of subjects classified high risk with the outcome of interest at each high risk threshold.

plot_clinical_impact(x, population.size = 1000, cost.benefit.axis = TRUE,
  n.cost.benefits = 6, cost.benefits, confidence.intervals, col = "black",
  lty = 1, lwd = 2, xlim, ylim, xlab, ylab,
  cost.benefit.xlab = "Cost:Benefit Ratio", legend.position = c("topright",
  "right", "bottomright", "bottom", "bottomleft", "left", "topleft", "top",
  "none"), ...)

`x`	decision_curve object to plot. Assumes output from function 'decision_curve'
`population.size`	Hypothetical population size (default 1000).
`cost.benefit.axis`	logical (default TRUE) indicating whether to print an additional x-axis showing relative cost:benefit ratios in addition to risk thresholds.
`n.cost.benefits`	number of cost:benefit ratios to print if cost.benefit.axis = TRUE (default n.cost.benefit = 6).
`cost.benefits`	Character vector of the form c("c1:b1", "c2:b2", ..., "cn:bn") with integers ci, bi corresponding to specific cost:benefit ratios to print. Default allows the function to calculate these automatically.
`confidence.intervals`	logical indicating whether to plot confidence intervals.
`col`	vector of length two indicating the color for the number high risk and the second to the number high risk with outcome, respectively.
`lty`	vector of linetypes. The first element corresponds to the number high risk and the second to the number high risk with outcome.
`lwd`	vector of linewidths. The first element corresponds to the number high risk and the second to the number high risk with outcome.
`xlim`	vector giving c(min, max) of x-axis. Defaults to c(min(thresholds), max(thresholds)).
`ylim`	vector giving c(min, max) of y-axis.
`xlab`	label of main x-axis.
`ylab`	label of y-axis.
`cost.benefit.xlab`	label of cost:benefit ratio axis.
`legend.position`	character vector giving position of legend. Options are "topright" (default), "right", "bottomright", "bottom", "bottomleft", "left", "topleft", "top", or "none".
`...`	other options directly send to plot()

#'data(dcaData)
set.seed(123)
baseline.model <- decision_curve(Cancer~Age + Female + Smokes,
                                data = dcaData,
                                thresholds = seq(0, .4, by = .001),
                                bootstraps = 25) #should use more bootstrap replicates in practice!

#plot the clinical impact
plot_clinical_impact(baseline.model, xlim = c(0, .4),
                    col = c("black", "blue"))