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

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

# Customized survival curves
p <- 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
)

p <- 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 = F,    ##不默认显示P
                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
)
##计算公式
data.survdiff <- survdiff(Surv(time, status) ~ sex,data = lung)
p.val = 1 - pchisq(data.survdiff$chisq, length(data.survdiff$n) - 1)
HR = (data.survdiff$obs[2]/data.survdiff$exp[2])/(data.survdiff$obs[1]/data.survdiff$exp[1])
up95 = exp(log(HR) + qnorm(0.975)*sqrt(1/data.survdiff$exp[2]+1/data.survdiff$exp[1]))
low95 = exp(log(HR) - qnorm(0.975)*sqrt(1/data.survdiff$exp[2]+1/data.survdiff$exp[1]))
ci <- paste0(sprintf("%.3f",HR)," [",sprintf("%.3f",low95),", ",sprintf("%.3f",up95),"]")

p$plot <- p$plot + 
  annotate("text", x = 0, y = 0.05, 
                            label = paste0("P value = ",sprintf("%.3f",p.val),"\n HR (95% CI) = ",ci),   ###添加P和HR 95%CI
                            size = 5, color = "black", hjust = 0)+
  theme(text = element_text(size = 15))
p$plot