The survminer R package provides functions for facilitating survival analysis and visualization. The current version contains the function ggsurvplot() for easily drawing beautiful survival curves using ggplot2. ggsurvplot() includes also some options for displaying the p-value and the 'number at risk' table, under the survival curves.
Find out more at http://www.sthda.com/english/wiki/survminer.
Install from CRAN as follow:
install.packages("survminer")Or, install the latest version from GitHub:
# Install
if(!require(devtools)) install.packages("devtools")
devtools::install_github("kassambara/survminer")# Loading
library("survminer")
# Loading required package: ggplot2#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Example 1: Survival curve with one group
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
require("survival")
# Loading required package: survival
fit <- survfit(Surv(time, status) ~ 1, data = lung)
ggsurvplot(fit, color = "#2E9FDF")
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Example 2: Survival curves with two groups
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Fit survival curves
#++++++++++++++++++++++++++++++++++++
require("survival")
fit<- survfit(Surv(time, status) ~ sex, data = lung)
# Drawing survival curves
ggsurvplot(fit)
# Change font style, size and color
#++++++++++++++++++++++++++++++++++++
# Change only font size
ggsurvplot(fit, main = "Survival curve",
font.main = 18,
font.x = 16,
font.y = 16,
font.tickslab = 14)
# Change font size, style and color at the same time
ggsurvplot(fit, main = "Survival curve",
font.main = c(16, "bold", "darkblue"),
font.x = c(14, "bold.italic", "red"),
font.y = c(14, "bold.italic", "darkred"),
font.tickslab = c(12, "plain", "darkgreen"))
# Legend: title, labels and position
#++++++++++++++++++++++++++++++++++++
# Change the legend title and labels
ggsurvplot(fit, legend = "bottom",
legend.title = "Sex",
legend.labs = c("Male", "Female"))
# Specify legend position by its coordinates
ggsurvplot(fit, legend = c(0.2, 0.2))
# format
#++++++++++++++++++++++++++++++++++++
# change line size --> 1
# Change line types by groups (i.e. "strata")
# and change color palette
ggsurvplot(fit, size = 1, # change line size
linetype = "strata", # change line type by groups
break.time.by = 250, # break time axis by 250
palette = c("#E7B800", "#2E9FDF"), # custom color palette
conf.int = TRUE, # Add confidence interval
pval = TRUE # Add p-value
)
# Use brewer color palette "Dark2"
ggsurvplot(fit, linetype = "strata",
conf.int = TRUE, pval = TRUE,
palette = "Dark2")
# Use grey palette
ggsurvplot(fit, linetype = "strata",
conf.int = TRUE, pval = TRUE,
palette = "grey")
# Add risk table
#++++++++++++++++++++++++++++++++++++
# Add risk table
# and change risk table y text colors by strata
ggsurvplot(fit, pval = TRUE, conf.int = TRUE,
risk.table = TRUE, risk.table.y.text.col = TRUE)
# Customize the output and then print
res <- ggsurvplot(fit, pval = TRUE, conf.int = TRUE,
risk.table = TRUE)
res$table <- res$table + theme(axis.line = element_blank())
res$plot <- res$plot + labs(title = "Survival Curves")
print(res)
# Change color, linetype by strata, risk.table color by strata
ggsurvplot(fit,
pval = TRUE, conf.int = TRUE,
risk.table = TRUE, # Add risk table
risk.table.col = "strata", # Change risk table color by groups
linetype = "strata", # Change line type by groups
ggtheme = theme_bw(), # Change ggplot2 theme
palette = c("#E7B800", "#2E9FDF"))
# Change x axis limits (xlim)
#++++++++++++++++++++++++++++++++++++
# One would like to cut axes at a specific time point
ggsurvplot(fit,
pval = TRUE, conf.int = TRUE,
risk.table = TRUE, # Add risk table
risk.table.col = "strata", # Change risk table color by groups
ggtheme = theme_bw(), # Change ggplot2 theme
palette = "Dark2",
xlim = c(0, 600))
# Survival curve transformation
#++++++++++++++++++++++++++++++++++++
# Plot cumulative events
ggsurvplot(fit, conf.int = TRUE,
palette = c("#FF9E29", "#86AA00"),
risk.table = TRUE, risk.table.col = "strata",
fun = "event")
# Plot the cumulative hazard function
ggsurvplot(fit, conf.int = TRUE,
palette = c("#FF9E29", "#86AA00"),
risk.table = TRUE, risk.table.col = "strata",
fun = "cumhaz")
# Arbitrary function
ggsurvplot(fit, conf.int = TRUE,
palette = c("#FF9E29", "#86AA00"),
risk.table = TRUE, risk.table.col = "strata",
pval = TRUE,
fun = function(y) y*100)
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Example 3: Survival curve with multiple group
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Fit (complexe) survival curves
#++++++++++++++++++++++++++++++++++++
require("survival")
fit2 <- survfit( Surv(time, status) ~ rx + adhere,
data = colon )
# Visualize
#++++++++++++++++++++++++++++++++++++
# Visualize: add p-value, chang y limits
# change color using brewer palette
ggsurvplot(fit2, pval = TRUE,
break.time.by = 400,
risk.table = TRUE)
# Adjust risk table and survival plot heights
# ++++++++++++++++++++++++++++++++++++
# Risk table height
ggsurvplot(fit2, pval = TRUE,
break.time.by = 400,
risk.table = TRUE,
risk.table.col = "strata",
risk.table.height = 0.5, # Useful when you have multiple groups
palette = "Dark2")
# Change legend labels
# ++++++++++++++++++++++++++++++++++++
ggsurvplot(fit2, pval = TRUE,
break.time.by = 400,
risk.table = TRUE,
risk.table.col = "strata",
ggtheme = theme_bw(),
legend.labs = c("A", "B", "C", "D", "E", "F"))