survminer (version 0.4.9)

ggsurvplot: Drawing Survival Curves Using ggplot2


ggsurvplot() is a generic function to plot survival curves. Wrapper around the ggsurvplot_xx() family functions. Plot one or a list of survfit objects as generated by the survfit.formula() and surv_fit functions:

See the documentation for each function to learn how to control that aspect of the ggsurvplot(). ggsurvplot() accepts further arguments to be passed to the ggsurvplot_xx() functions. Has options to:

  • plot a list of survfit objects,

  • facet survival curves into multiple panels,

  • group dataset by one or two grouping variables and to create the survival curves in each subset,

  • combine multiple survfit objects into one plot,

  • add survival curves of the pooled patients (null model) onto the main stratified plot,

  • plot survival curves from a data frame containing survival curve summary as returned by surv_summary().


  data = NULL,
  fun = NULL,
  color = NULL,
  palette = NULL,
  linetype = 1, = FALSE,
  pval = FALSE,
  pval.method = FALSE,
  test.for.trend = FALSE,
  surv.median.line = "none",
  risk.table = FALSE,
  cumevents = FALSE,
  cumcensor = FALSE,
  tables.height = 0.25, = NULL, = NULL,
  add.all = FALSE,
  combine = FALSE,
  ggtheme = theme_survminer(),
  tables.theme = ggtheme,

# S3 method for ggsurvplot print( x, surv.plot.height = NULL, risk.table.height = NULL, ncensor.plot.height = NULL, newpage = TRUE, ... )


return an object of class ggsurvplot which is list containing the following components:

  • plot: the survival plot (ggplot object)

  • table: the number of subjects at risk table per time (ggplot object).

  • cumevents: the cumulative number of events table (ggplot object).

  • ncensor.plot: the number of censoring (ggplot object).

  • data.survplot: the data used to plot the survival curves (data.frame).

  • data.survtable: the data used to plot the tables under the main survival curves (data.frame).


Customize survival plots and tables. See also ggsurvplot_arguments.

Plot title and axis labels

  • title: main title.

  • xlab, ylab: x and y axis labels, respectively.

Legend title, labels and position

  • legend: character specifying legend position. Allowed values are one of c("top", "bottom", "left", "right", "none"). Default is "top" side position. to remove the legend use legend = "none". Legend position can be also specified using a numeric vector c(x, y). In this case it is possible to position the legend inside the plotting area. x and y are the coordinates of the legend box. Their values should be between 0 and 1. c(0,0) corresponds to the "bottom left" and c(1,1) corresponds to the "top right" position. For instance use legend = c(0.8, 0.2).

  • legend.title: legend title.

  • legend.labs: character vector specifying legend labels. Used to replace the names of the strata from the fit. Should be given in the same order as those strata.

Axis limits, breaks and scales

  • numeric value controlling time axis breaks. Default value is NULL.

  • alias of Numeric value controlling x axis breaks. Default value is NULL.

  • same as but for y axis.

  • surv.scale: scale transformation of survival curves. Allowed values are "default" or "percent".

  • xscale: numeric or character value specifying x-axis scale.

    • If numeric, the value is used to divide the labels on the x axis. For example, a value of 365.25 will give labels in years instead of the original days.

    • If character, allowed options include one of - "d_m", "d_y", "m_d", "m_y", "y_d" and "y_m" - where d = days, m = months and y = years. For example, xscale = "d_m" will transform labels from days to months; xscale = "m_y", will transform labels from months to years.

  • xlim,ylim: x and y axis limits e.g. xlim = c(0, 1000), ylim = c(0, 1).

  • axes.offset: logical value. Default is TRUE. If FALSE, set the plot axes to start at the origin.

Confidence interval

  • fill color to be used for confidence interval.

  • confidence interval style. Allowed values include c("ribbon", "step").

  • numeric value specifying confidence fill color transparency. Value should be in [0, 1], where 0 is full transparency and 1 is no transparency.


  • pval.size: numeric value specifying the p-value text size. Default is 5.

  • pval.coord: numeric vector, of length 2, specifying the x and y coordinates of the p-value. Default values are NULL.

  • pval.method.size: the same as pval.size but for displaying log.rank.weights name.

  • pval.method.coord: the same as pval.coord but for displaying log.rank.weights name.

  • log.rank.weights: the name for the type of weights to be used in computing the p-value for log-rank test. By default survdiff is used to calculate regular log-rank test (with weights == 1). A user can specify "1", "n", "sqrtN", "S1", "S2", "FH" to use weights specified in comp, so that weight correspond to the test as : 1 - log-rank, n - Gehan-Breslow (generalized Wilcoxon), sqrtN - Tarone-Ware, S1 - Peto-Peto's modified survival estimate, S2 - modified Peto-Peto (by Andersen), FH - Fleming-Harrington(p=1, q=1).

Median survival

  • surv.median.line: character vector for drawing a horizontal/vertical line at median survival. Allowed values include one of c("none", "hv", "h", "v"). v: vertical, h:horizontal.

Censor points

  • censor: logical value. If TRUE (default), censors will be drawn.

  • censor.shape: character or numeric value specifying the point shape of censors. Default value is "+" (3), a sensible choice is "|" (124).

  • censor.size: numveric value specifying the point size of censors. Default is 4.5.

Survival tables

General parameters for all tables. The arguments below, when specified, will be applied to all survival tables at once (risk, cumulative events and cumulative censoring tables).

  • tables.col: color to be used for all tables under the main plot. Default value is "black". If you want to color by strata (i.e. groups), use tables.col = "strata".

  • fontsize: font size to be used for the risk table and the cumulative events table.

  • character vector specifying text element font family, e.g.: = "Courier New".

  • tables.y.text: logical. Default is TRUE. If FALSE, the y axis tick labels of tables will be hidden.

  • tables.y.text.col: logical. Default value is FALSE. If TRUE, the y tick labels of tables will be colored by strata.

  • tables.height: numeric value (in [0 - 1]) specifying the general height of all tables under the main survival plot. Increase the value when you have many strata. Default is 0.25.

Specific to the risk table

  • risk.table.title: the title to be used for the risk table.

  • risk.table.pos: character vector specifying the risk table position. Allowed options are one of c("out", "in") indicating 'outside' or 'inside' the main plot, respectively. Default value is "out".

  • risk.table.col, risk.table.fontsize, risk.table.y.text, risk.table.y.text.col and risk.table.height: same as for the general parameters but applied to the risk table only.

Specific to the number of cumulative events table (cumevents)

  • cumevents.title: the title to be used for the cumulative events table.

  • cumevents.col, cumevents.y.text, cumevents.y.text, cumevents.height: same as for the general parameters but for the cumevents table only.

Specific to the number of cumulative censoring table (cumcensor)

  • cumcensor.title: the title to be used for the cumcensor table.

  • cumcensor.col, cumcensor.y.text, cumcensor.y.text.col, cumcensor.height: same as for the general parameters but for cumcensor table only.

Survival plot height

  • surv.plot.height: the height of the survival plot on the grid. Default is 0.75. Ignored when risk.table = FALSE.

Number of censored subjects barplot

  • ncensor.plot: logical value. If TRUE, the number of censored subjects at time t is plotted. Default is FALSE. Ignored when cumcensor = TRUE.

  • ncensor.plot.title: the title to be used for the censor plot. Used when ncensor.plot = TRUE.

  • ncensor.plot.height: the height of the censor plot. Used when ncensor.plot = TRUE.

Other graphical parameters

The plot can be easily customized using additional arguments to be passed to the function ggpar().

These arguments include font.title, font.subtitle, font.caption, font.x, font.y, font.tickslab and font.legend, which are vectors of length 3 indicating respectively the size (e.g.: 14), the style (e.g.: "plain", "bold", "italic", "bold.italic") and the color (e.g.: "red") of main title, subtitle, caption, xlab and ylab, axis tick labels and legend, respectively. For example font.x = c(14, "bold", "red").

Use font.x = 14, to change only font size; or use font.x = "bold", to change only font face.


  • Color palettes: The argument palette can be used to specify the color to be used for each group. By default, the first color in the palette is used to color the first level of the factor variable. This default behavior can be changed by assigning correctly a named vector. That is, the names of colors should match the strata names as generated by the ggsurvplot() function in the legend.


Run this code
# Example 1: Survival curves with two groups

# Fit survival curves
fit<- survfit(Surv(time, status) ~ sex, data = lung)

# Basic survival curves
ggsurvplot(fit, data = lung)

# Customized survival curves
ggsurvplot(fit, data = lung,
 surv.median.line = "hv", # Add medians survival

 # Change legends: title & labels
 legend.title = "Sex",
 legend.labs = c("Male", "Female"),
 # Add p-value and tervals
 pval = TRUE, = TRUE,
 # Add risk table
 risk.table = TRUE,
 tables.height = 0.2,
 tables.theme = theme_cleantable(),

 # Color palettes. Use custom color: c("#E7B800", "#2E9FDF"),
 # or brewer color (e.g.: "Dark2"), or ggsci color (e.g.: "jco")
 palette = c("#E7B800", "#2E9FDF"),
 ggtheme = theme_bw() # Change ggplot2 theme

# Change font size, style and color
# }
# Change font size, style and color at the same time
ggsurvplot(fit, data = lung,  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"))
# }

# Example 2: Facet ggsurvplot() output by
# a combination of factors

# Fit (complexe) survival curves
# }
fit3 <- survfit( Surv(time, status) ~ sex + rx + adhere,
                data = colon )

# Visualize
ggsurv <- ggsurvplot(fit3, data = colon,
  fun = "cumhaz", = TRUE,
  risk.table = TRUE, risk.table.col="strata",
  ggtheme = theme_bw())

# Faceting survival curves
curv_facet <- ggsurv$plot + facet_grid(rx ~ adhere)

# Faceting risk tables:
# Generate risk table for each facet plot item
ggsurv$table + facet_grid(rx ~ adhere, scales = "free")+
 theme(legend.position = "none")

 # Generate risk table for each facet columns
tbl_facet <- ggsurv$table + facet_grid(.~ adhere, scales = "free")
tbl_facet + theme(legend.position = "none")

# Arrange faceted survival curves and risk tables
g2 <- ggplotGrob(curv_facet)
g3 <- ggplotGrob(tbl_facet)
min_ncol <- min(ncol(g2), ncol(g3))
g <- gridExtra::gtable_rbind(g2[, 1:min_ncol], g3[, 1:min_ncol], size="last")
g$widths <- grid::unit.pmax(g2$widths, g3$widths)

# }
# Customized p-value
ggsurvplot(fit, data = lung, pval = TRUE)
ggsurvplot(fit, data = lung, pval = 0.03)
ggsurvplot(fit, data = lung, pval = "The hot p-value is: 0.031")

# }

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