I want to develop a prediction model (Cox PH) for all-cause mortality in a dataset of participants of whom (almost) all have died at the end of follow-up (e.g. 1-year).

Instead of predicting the absolute risk of dying at a certain timepoint, I would like to predict the survival time (in months) for each individual.

Is it possible to obtain such predictions in R (from e.g. a coxph-object) and, if yes, how can I do that?

Many thanks in advance!

**Answer**

The Cox Proportional Hazards model doesn’t model the underlying hazard, which is what you’d need to predict survival time like that – this is both the model’s great strength and one of it’s major drawbacks.

If you are particularly interested in obtaining estimates of the probability of survival at particular time points, I would point you towards parametric survival models (aka accelerated failure time models). These are implemented in the `survival`

package for R, and will give you parametric survival time distributions, wherein you can simply plug in the time you are interested in and get back a survival probability.

**Attribution***Source : Link , Question Author : Rob , Answer Author : Fomite*