r - 如何运行 Kaplan-Meier (KM) 分析来确定两组之间的生存差异？

Question

我想通过组合 group 变量和 ann 文件来创建数据矩阵。然后，我想运行 Kaplan-Meier (KM) 分析，以确定两组之间的生存率(即 1 与 0)相对于状态(活着或死亡)是否存在差异。我想从卡方测试输出中提取 p 值。

例如:

library(survival)
library(tidyverse)
library(survminer)

df <- x %>%  
  rename(status=vital_status,
         time=months_to_event) %>% 
  mutate(status=case_when(status=="LIVING" ~ 0,
                            status=="DECEASED" ~ 1))

f <- survdiff(Surv(time,status)~group, data=df)

plot(f,lwd=2,xlab='Weeks',ylab='S_hat(t)',main='KM Plots for Survival data')

Error in xy.coords(x, y, xlabel, ylabel, log) : 'x' is a list, but does not have components 'x' and 'y'

> dput(f)
structure(list(n = structure(c(`group=0` = 86L, `group=1` = 30L
), .Dim = 2L, .Dimnames = list(groups = c("group=0", "group=1"
)), class = "table"), obs = c(27, 5), exp = c(22.3862602609156, 
9.61373973908443), var = structure(c(6.62091719145294, -6.62091719145294, 
-6.62091719145294, 6.62091719145294), .Dim = c(2L, 2L)), chisq = 3.21505219963876, 
    na.action = structure(c(`89` = 76L, `124` = 105L, `129` = 110L
    ), class = "omit"), call = survdiff(formula = Surv(time, 
        status) ~ group, data = df)), class = "survdiff")

Answer 1

library(tidyverse)
library(survival)
library(survminer)

df1 <- df %>%  
  rename(status = vital_status,
         time = months_to_event) %>% 
  mutate(status = case_when(status=="LIVING" ~ 0,
                            status=="DECEASED" ~ 1))


f1 <- survfit(Surv(time, status) ~ group, data = df1)
ggsurvplot(f1,
           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
           surv.median.line = "hv", # Specify median survival
           ggtheme = theme_bw(), # Change ggplot2 theme
           palette = c("#E7B800", "#2E9FDF"))