生存分析新技能:小洁老师带你全代码实现生存曲线与风险表的完美融合

library(survival)
library(survminer)
#> Loading required package: ggplot2
#> Loading required package: ggpubr
#> 
#> Attaching package: 'survminer'
#> The following object is masked from 'package:survival':
#> 
#>     myeloma
ls("package:survminer")
#>  [1] "%++%"                "arrange_ggsurvplots" "BMT"                
#>  [4] "BRCAOV.survInfo"     "ggadjustedcurves"    "ggcompetingrisks"   
#>  [7] "ggcoxdiagnostics"    "ggcoxfunctional"     "ggcoxzph"           
#> [10] "ggcumcensor"         "ggcumevents"         "ggflexsurvplot"     
#> [13] "ggforest"            "ggrisktable"         "ggsurvevents"       
#> [16] "ggsurvplot"          "ggsurvplot_add_all"  "ggsurvplot_combine" 
#> [19] "ggsurvplot_df"       "ggsurvplot_facet"    "ggsurvplot_group_by"
#> [22] "ggsurvplot_list"     "ggsurvtable"         "myeloma"            
#> [25] "pairwise_survdiff"   "surv_adjustedcurves" "surv_categorize"    
#> [28] "surv_cutpoint"       "surv_fit"            "surv_group_by"      
#> [31] "surv_median"         "surv_pvalue"         "surv_summary"       
#> [34] "theme_cleantable"    "theme_survminer"

?ggsurvplot

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"))

## End(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::gtable_rbind(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)

## End(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")

require("survival")
fit<- survfit(Surv(time, status) ~ sex, data = lung)

# Customized survival curves
a = 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
)

class(a$plot)
#> [1] "gg"     "ggplot"
class(a$table)
#> [1] "gg"     "ggplot"

#a$table和a$plot都是ggplot格式的图，那么是否将这两个图拼起啦？试一试：

library(patchwork)
a$plot / a$table

ggsave("sur.pdf")
#> Saving 7 x 5 in image