Failed to build kaplan-meier curve with survifit object from list using ggsurvplot

Question

I am trying to build a Kaplan-Mayer curve using ggsurvplot from a surrogate package. I cannot build it when I pass in the survivor object saved in the list.

Let me use the lung dataset as an example. Everything works below:

library("survival")
library("survminer")
fit <- survfit(Surv(time, status) ~ sex, data = lung)
ggsurvplot(fit,
          conf.int = TRUE,
          risk.table.col = "strata", 
          palette = c("#E7B800", "#2E9FDF"),
          xlim = c(0, 600))

Now I save two variables and save the model result in a list. Then I tried to make a KM chart with ggsurvplot.

vars <- c('sex', 'ph.ecog')
l<- map (vars, ~survfit(Surv(time, status)~ get(.x),data = lung ))
l<- set_names(l, vars)
ggsurvplot(l$sex,
          conf.int = TRUE,
          risk.table.col = "strata", 
          palette = c("#E7B800", "#2E9FDF"),
          xlim = c(0, 600))

I received the error message as follows:

Error in eval(inp, data, env) : object '.x' not found

Does anyone know why? How can I fix this problem? Many thanks!

Answer 1

. , , R , , , tidyverse , .

 library(tidyverse)
 # run both your code segments, since you will need a small piece of first one
str(l$sex)
List of 14
 $ n        : int [1:2] 138 90
 $ time     : num [1:206] 11 12 13 15 26 30 31 53 54 59 ...
 $ n.risk   : num [1:206] 138 135 134 132 131 130 129 128 126 125 ...
 $ n.event  : num [1:206] 3 1 2 1 1 1 1 2 1 1 ...
 $ n.censor : num [1:206] 0 0 0 0 0 0 0 0 0 0 ...
 $ surv     : num [1:206] 0.978 0.971 0.957 0.949 0.942 ...
 $ type     : chr "right"
 $ strata   : Named int [1:2] 119 87
  ..- attr(*, "names")= chr [1:2] "get(.x)=1" "get(.x)=2"
 $ std.err  : num [1:206] 0.0127 0.0147 0.0181 0.0197 0.0211 ...
 $ upper    : num [1:206] 1 0.999 0.991 0.987 0.982 ...
 $ lower    : num [1:206] 0.954 0.943 0.923 0.913 0.904 ...
 $ conf.type: chr "log"
 $ conf.int : num 0.95
 $ call     : language survfit(formula = Surv(time, status) ~ get(.x), data = lung)
 - attr(*, "class")= chr "survfit"

, , strata "names" -attribute, get( - , , ggsurvplot. attr<-, - ( less- "language-y" ).

attr(l[['sex']][['strata']], "names") <- c("sex=1", "sex=2")

"call" -leaf, - . , , "call" leaf from the first fit`-object yoiu:

l$sex$call <- fit$call
ggsurvplot(l$sex,
          conf.int = TRUE,
          risk.table.col = "strata", 
          palette = c("#E7B800", "#2E9FDF"),
          xlim = c(0, 600))