In ggobi/ggally: Extension to 'ggplot2'

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(GGally)

`GGally::ggsurv()`

This function produces Kaplan-Meier plots using ggplot2. As a first argument, ggsurv() needs a survival::survfit() object. Default settings differ for single stratum and multiple strata objects.

Single Stratum

require(ggplot2)
require(survival)
require(scales)

data(lung, package = "survival")
sf.lung <- survival::survfit(Surv(time, status) ~ 1, data = lung)
ggsurv(sf.lung)

Multiple Stratum

The legend color positions matches the survival order or each stratum, where the stratums that end at a lower value or time have a position that is lower in the legend.

sf.sex <- survival::survfit(Surv(time, status) ~ sex, data = lung)
pl.sex <- ggsurv(sf.sex)
pl.sex

Alterations

Since a ggplot2 object is returned, plot objects may be altered after the original creation.

Adjusting the legend

pl.sex +
  ggplot2::guides(linetype = "none") +
  ggplot2::scale_colour_discrete(
    name   = "Sex",
    breaks = c(1, 2),
    labels = c("Male", "Female")
  )

Adjust the limits

data(kidney, package = "survival")
sf.kid <- survival::survfit(Surv(time, status) ~ disease, data = kidney)
pl.kid <- ggsurv(sf.kid, plot.cens = FALSE)
pl.kid

# Zoom in to first 80 days
pl.kid + ggplot2::coord_cartesian(xlim = c(0, 80), ylim = c(0.45, 1))

Add text and remove the legend

pl.kid +
  ggplot2::annotate(
    "text",
    label = c("PKD", "Other", "GN", "AN"),
    x = c(90, 125, 5, 60),
    y = c(0.8, 0.65, 0.55, 0.30),
    size = 5,
    colour = scales::hue_pal(
      h         = c(0, 360) + 15,
      c         = 100,
      l         = 65,
      h.start   = 0,
      direction = 1
    )(4)
  ) +
  ggplot2::guides(color = "none", linetype = "none")