Median Survival Time for Clinical Trials I have a Clinical Trial where I'll be comparing a drug vs placebo.
Then I intend to run a Log-rank test on it.
Now for the sample size calculations, I would be requiring the hazard ratio and the median survival time for the treatement and placebo.
Now my confusion is that how would I get the median survival time without the dataset, beforehand ?
Do I need to consult previous studies to find the median survival for treatement and placebo or is there any other method.
Please help me with my confusion.

Don't use a log-rank test.  This is just a special case of the Cox proportional hazards model and doesn't allow for covariate adjustment.  You need to adjust for pre-specified predictors that explain a clinically important amount of outcome variation to get the proportional hazards assumption to be better satisfied.
The power for a comparison using the Cox model (and hence also using the log-rank test) is not a function of the median survival time.  It is a function of the expected number of events in the first group and the expected number of events in the second group.  To get the expected number of events you need to make various assumptions, usually based on the cumulative incidence at a fixed time point.  The R Hmisc package cpower and especially the spower functions help.  spower does a clinical trial simulation where various complexities can be handled (non-constant hazard ratio, non-constant hazard ratio, complex accrual rate variation, etc.).
