# NOT RUN {
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Example 1: Survival curves with two groups
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Fit survival curves
#++++++++++++++++++++++++++++++++++++
require("survival")
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,
conf.int = 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
#++++++++++++++++++++++++++++++++++++
# }
# NOT RUN {
# 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"))
# }
# NOT RUN {
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Example 2: Facet ggsurvplot() output by
# a combination of factors
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Fit (complexe) survival curves
#++++++++++++++++++++++++++++++++++++
# }
# NOT RUN {
require("survival")
fit3 <- survfit( Surv(time, status) ~ sex + rx + adhere,
data = colon )
# Visualize
#++++++++++++++++++++++++++++++++++++
ggsurv <- ggsurvplot(fit3, data = colon,
fun = "cumhaz", conf.int = TRUE,
risk.table = TRUE, risk.table.col="strata",
ggtheme = theme_bw())
# Faceting survival curves
curv_facet <- ggsurv$plot + facet_grid(rx ~ adhere)
curv_facet
# Faceting risk tables:
# Generate risk table for each facet plot item
ggsurv$table + facet_grid(rx ~ adhere, scales = "free")+
theme(legend.position = "none")
# Generate risk table for each facet columns
tbl_facet <- ggsurv$table + facet_grid(.~ adhere, scales = "free")
tbl_facet + theme(legend.position = "none")
# Arrange faceted survival curves and risk tables
g2 <- ggplotGrob(curv_facet)
g3 <- ggplotGrob(tbl_facet)
min_ncol <- min(ncol(g2), ncol(g3))
g <- gridExtra::rbind.gtable(g2[, 1:min_ncol], g3[, 1:min_ncol], size="last")
g$widths <- grid::unit.pmax(g2$widths, g3$widths)
grid::grid.newpage()
grid::grid.draw(g)
# }
# NOT RUN {
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Example 3: CUSTOMIZED PVALUE
#%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# 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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