Visualizing the Cox model

Survival Analysis in R

Heidi Seibold

Statistician at LMU Munich

Steps to visualize a Cox model

  • Compute Cox model
  • Decide on covariate combinations ("imaginary patients")
  • Compute survival curves
  • Create data.frame with survival curve information
  • Plot
Survival Analysis in R

Step 1: Compute Cox model

cxmod <- coxph(Surv(time, cens) ~ horTh + tsize, data = GBSG2)
  • Decide on covariate combinations ("imaginary patients")
    newdat <- expand.grid(
      horTh = levels(GBSG2$horTh),
      tsize = quantile(GBSG2$tsize, probs = c(0.25, 0.5, 0.75))   )
    rownames(newdat) <- letters[1:6]
    newdat
    
  horTh tsize
a    no    20
b   yes    20
c    no    25
...
Survival Analysis in R

Step 2: Compute survival curves

cxsf <- survfit(cxmod, data = GBSG2, newdata = newdat, conf.type = "none")

str(cxsf)
List of 10
$ n       : int 686
$ time    : num [1:574] 8 15 16 17 18 29 42 46 57 63 ...
$ n.risk  : num [1:574] 686 685 684 683 681 680 679 678 677 676 ...
$ n.event : num [1:574] 0 0 0 0 0 0 0 0 0 0 ...
$ n.censor: num [1:574] 1 1 1 2 1 1 1 1 1 1 ...
$ surv    : num [1:574, 1:6] 1 1 1 1 1 1 1 1 1 1 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : NULL
.. ..$ : chr [1:6] "a" "b" "c" "d" ...
$ type    : chr "right"
$ cumhaz  : num [1:574, 1:6] 0 0 0 0 0 0 0 0 0 0 ...
$ std.err : num [1:574, 1:6] 0 0 0 0 0 0 0 0 0 0 ...
$ call    : language survfit(formula = cxmod, newdata = newdat, conf.type = "none", data = GBSG2)
  - attr(*, "class")= chr [1:2] "survfit.cox" "survfit"
Survival Analysis in R

Step 3: Create data.frame with survival curve information

surv_cxmod0 <- surv_summary(cxsf)
head(surv_cxmod0)
   time n.risk n.event n.censor surv std.err upper lower strata
 1    8    686       0        1    1       0    NA    NA      a
 2   15    685       0        1    1       0    NA    NA      a
 3   16    684       0        1    1       0    NA    NA      a
 4   17    683       0        2    1       0    NA    NA      a
 5   18    681       0        1    1       0    NA    NA      a
 6   29    680       0        1    1       0    NA    NA      a
surv_cxmod <- cbind(surv_cxmod0,
                    newdat[as.character(surv_cxmod0$strata), ])
Survival Analysis in R

Step 4: Plot

ggsurvplot_df(surv_cxmod, linetype = "horTh", color = "tsize",
  legend.title = NULL, censor = FALSE)

Survival Analysis in R

Now it's your turn to visualize!

Survival Analysis in R

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