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Upon doing:

kmsurvival <<- survfit(Surv(time, event) ~ Risk)

I get a KM plot similar to :

KM Plot

Now, for a particular patient in the data; say patient number 15, can I find out his/her probability of survival at a given time, using the kaplan meier estimate?

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You have to see in which groups this patient is, and then do

kmsurvival <- survfit(Surv(time, event) ~ Risk)
summary(kmsurvival, times = 40)

to get the survival probability at 40 (days?). If you want to condition on additional information for that patient (e.g., age, sex, BMI, etc.), you would need to fit a Cox model and get the estimated survival probability from it (though under the proportional hazards assumption).

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  • $\begingroup$ Say patient 2,5,3 fall in group1. How does the above solution specifically let me see probability of survival for patient number 2 after 40 months? $\endgroup$ – rj dj Sep 13 '18 at 12:39
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    $\begingroup$ For patients in the same group, the survival probabilities will be the same. You don't use any other information for them. $\endgroup$ – Dimitris Rizopoulos Sep 13 '18 at 13:16

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