CODEWITHSUNDEEP
ggplot2plotsurvival-analysiscox-regressionsurvival
Sveta
Sveta

Reputation: 1

Number at risk for cox regression plot

can I make "number at risk "table for cox plot if I have more than one independent variable? if it possible where can I find the relevant code (I searched but couldn't find) the code I used on my data:

fit <- coxph(Surv(time,event) ~chr1q21_status+CCND1+CRTM1+IRF4,data = myeloma)

ggsurvplot(fit, data = myeloma,
  risk.table=TRUE, break.time.by=365, xlim = c(0,4000),
  risk.table.y.text=FALSE, legend.labs =  c("2","3","4+"))

got this message- object 'ggsurv' not found' although for only one variable and the function survfit it worked.

Upvotes: 0

Views: 1442

Answers (1)

alan ocallaghan
alan ocallaghan

Reputation: 3038

"number at risk "table for cox plot

It's not a Cox plot, it's a Kaplan-Meier plot. You're trying to plot a Cox model, when what you want is to fit KM curves using survfit and then to plot the resulting fit:

library("survival")
library("survminer")
fit <- survfit(Surv(time,status) ~ ph.ecog + sex , data = lung)
ggsurvplot(fit, data = lung, risk.table = TRUE)

Since you now mention that you have continuous predictors, perhaps you could think about what you expect an at-risk table or KM plot to show. Here's an example of binning a continuous measure (age):

library("survival")
library("survminer")
#> Loading required package: ggplot2
#> Loading required package: ggpubr
#> Loading required package: magrittr
lung$age_bin <- cut(lung$age, quantile(lung$age))
fit <- survfit(Surv(time,status) ~ age_bin + sex , data = lung)
ggsurvplot(fit, data = lung, risk.table = TRUE)

Upvotes: 0

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