There are several ways to do this in R. One is to use the
survest function in the
rms package in conjunction with that package's
Lift charts are not used to validate models but instead to find the subset of higher risk individuals will get you the biggest bang for the buck. Lift charts do not use deciles or other binning methods but deal with continuous predictions. You can even make a lift chart on the relative log hazard scale without bothering to compute cumulative risks.
It may not be a good idea to compute how many events you can capture per se, as these are functions of the censoring distribution, but rather to estimate the proportion of cumulative risk that be captured with a subset of high-risk subjects.