No, macro is unnecessary if you're not going to reuse the code.
Basically you use PROC survyselect to draw samples, then merge in the covariates, and run Cox model with by-group processing to obtain a bootstrapping confidence interval for hazard ratio or whatsoever.
My feeling is that resampling with replacement is preferred if your sample size is close or greater than the # of subjects so at least some samples can avoid the outliers or whatever. I could be wrong.

SAS procedure is simple. The following example will generate 10 sampling sets. You need a text book for what is bootstrap sampling.

proc surveyselect data=sashelp.class out=outboot
seed=123456
method=urs
samprate=1
outhits
rep=10;
run;

proc print;run;

Thanks so much for your help~ really appreciate it!
I tried proc surveyselect with 1000 times resampling, and my pc crashed..
The percentages of missing data was the same high as the original data.. So if I need multiple imputations to handle missing data in the bootstrap sampling, my pc will definitely be dead again..

So can I ask: normally you will deal with missing data before or after the bootstrap resampling?
Big thanks and regards~

Nice reply! Thanks for your patience and help!!