Hello everyone,

I am doing a fairly large population study to estimate the treatment effect of a drug in a particular patient group. More specifically, I would like to compare the average age at death for patients that do use this drug vs patients that do not.

One approach I am considering is using propensity score matching to match both groups with their healthy counterparts (which do not use the drug) based on several variables to see what the treatment effect is in both groups. Another approach I have seen is a Kaplan–Meier analysis with a log rank test. Some advice on the best approach would be highly appreciated.

Also, one issue that I am stumbling upon is that most of the subjects are still alive and currently the average age at death is slightly below the average age of the population. Would this be a problem?