Faceted Kaplan-Meier plot

Usage

km_plot(
  df,
  coxmodel,
  facet = NULL,
  ...,
  maxtime = NULL,
  ylab = if (!invert) "surviving (%)" else "affected (%)",
  xlab = "time (days)",
  facetlab = NULL,
  ylim = (if (invert) c(0, NA) else c(NA, 100)),
  n_breaks = 5,
  heights = c(10, 1),
  invert = FALSE,
  show_label = FALSE,
  show_legend = TRUE
)

Arguments

df

the data

coxmodel

the cox model output of survival::coxph from the data

facet

the division to highlight in the KM strata. Defaults to first term on the lhs of the cox model formula

...

Named arguments passed on to survival::survfit

formula: either a formula or a previously fitted model
...: other arguments to the specific method

maxtime

the longest x value to plot (optional)

ylab

the y axis label

xlab

the x axis label

facetlab

a label to add as a facet title

ylim

the range to show on the KM plot

n_breaks

number of x axis breaks to display this also determines the timing and number of "at risk" counts to display.

heights

the relative height between the KM plot and the "at risk" table

invert

reverse survival statistics to count number of affected

show_label

show the label on the at risk table ( which is somewhat redundant as items are coloured)

show_legend

show the legend for the strata. (This is sometimes redundant if the at risk table is labelled)

Value

a ggplot patchwork.

Examples


cox = survival::coxph(survival::Surv(time, status) ~ trt + celltype + karno +
  diagtime + age + prior , data = survival::veteran)

km_plot(survival::veteran, cox)

km_plot(survival::veteran, cox, facet = 1)


km_plot(survival::veteran, cox, "celltype", show_label=TRUE) &
   ggplot2::theme(legend.position="bottom")


km_plot(survival::veteran, cox, "trt", show_label=TRUE) &
   ggplot2::theme(legend.position="bottom")