Kaplan Meier analysis: 95% CI wider in R than in SAS

Hello All,
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Am replicating in R an analysis I did earlier using SAS. See this as a test of whether I'm ready to start using R in my day-to-day work.
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Just finished replicating a Kaplan Meier analysis. Everything seems to work out fine except for one thing. The 95% CI around my estimate for the median is substantially larger in R than in SAS. For example, in SAS I have a median of 3.29 with a 95% CI of [1.15, 5.29]. In R, I get a median of 3.29 with a 95% CI of [1.35,?13.35].
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Can anyone tell me why I get this difference?
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My R code looks like:
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survfrm <- Surv(progression_months_landmark_14,progression==1) ~ pr_rg_landmark_14 
survobj <- survfit(survfrm, data=Survival)
survlrk <- survdiff(survfrm, data=Survival)
summary(survobj)
print(survobj)
print(survlrk)
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My SAS code looks like:
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proc lifetest data=survival;
strata pr_rg_landmark_14;
time progression_months_landmark_14 * progression(0);
run;

Thought maybe the difference could have something to do with the strata statement in the SAS code not being translated properly into R. Tried changing my R code to make pr_rg_landmark_14 a strata but this didn't seem to change anything. Except that I no longer got a log rank test. 

Thanks,

Paul
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