Obtaining Time-to-Event Analysis Statistics

Time-to-event analysis in clinical trials is concerned with comparing the distributions of time to some event for various treatment regimens. The two nonparametric tests used to compare distributions are the log-rank test and the Cox proportional hazards model. The Cox proportional hazards model is more useful when you need to adjust your model for covariates. 

Let s assume that you are comparing the two treatment groups of Active Drug and Placebo to see if they display different distributions for time to death. You can run this analysis with PROC LIFETEST as follows  

Here we assume that the daystodeath variable is the number of days to death or last known date alive for the patient. The deathcensor variable value is 1 if the patient died and 0 if the patient did not die. The p-value variable for the log-rank test is called ProbChiSq in the pvalue data set where the Test variable equals Log-Rank.  

Now let s assume that you want to adjust for gender as a covariate in your comparison of time to death. You can use PROC PHREG to put gender into your model like this  

Note that with PROC PHREG all covariates need to be numeric, so treatment and gender need to be numeric. The p-values and hazard ratios that are useful for your statistical tables can be found in the ProbChiSq and HazardRatio variables, respectively, in the pvalue data set. 

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