Very high hazard ratio from Proc Phreg

[SAS_User]

I ran proc lfietest to generate KM curves using the following code:

proc lifetest data= dat;

time Survival*censor(1) ;
strata group   /test=(logrank);
run;

Since I wanted the hazard ratios for this, I ran the following Proc Phreg code:

proc phreg data=dat;
class group;
model Survival*censor(1) =group ;
run;

The HR came out to be very high -a seven digit number (3797239) and not significant - pvalue=0.99. Can someone help me understand this?

Thanks so much!

[Reeza]

Can you post a PROC means on your survival time BY group and by censor. I suspect the proportionality assumption is violated for one thing, I think the ASSESS statement can be used to check this assumption. 

If you could post the results that would be helpful. 

[SAS_User]

Thank you so much for helping with this. Any insight you could give with this is highly appreciated since I only have a couple of hours to deliver these HRs

Here are the Proc means: (I will be checking assess shortly)

The MEANS Procedure
Group=No
Analysis Variable : Survival Time [Days]
N	Mean	Std Dev	Minimum	Maximum
107	756.79	355.51	9	1246
Group=Yes
Analysis Variable : Survival Time [Days]
N	Mean	Std Dev	Minimum	Maximum
35	868.8	242.74	250	1141
The MEANS Procedure
Censoring variable =No
Analysis Variable : Survival Time [Days]
N	Mean	Std Dev	Minimum	Maximum
16	406.88	158.85	196	701
Censoring variable =Yes
Analysis Variable : Survival Time [Days]
N	Mean	Std Dev	Minimum	Maximum
126	832.33	319.79	9	1246

[Reeza]

You only have 16 uncensored events? That's a small rate which is contributing to the issue. Especially when you then break it down into groups as well. 

[SAS_User]

Thanks

Attached is also the KM plot as well... 

What would be a good clinical or statistical reason for not reporting the hazard ratio?

[Reeza]

It appears the Proportionality assumption required for a Cox regression is violated. This is compounded by the fact that you have very low event rates and really not a lot of observations. Therefore estimates from this data would have a large degree of uncertainty around  them. 

[SAS_User]

Thank you so much for the help. I will update later on running assess statement

[JacobSimonsen]

Such big estimates only occur when the model doesnt converge. I think that there is no uncensored events in one of the two groups. It can even occur if there is uncensored events in both groups, but only if all uncensored events in one group comes when all persons in the other group are no longer in risk.

Try make the proc means again with censoring and group at the same time in the by statement.

I dont think it has to do with the the assumption of the proportionality statement.

[SAS_User]

Thanks for your comments. Here are the mean measures:

The MEANS Procedure
Censoring variable=No Group=No
Survival Time [Days]
N	Mean	Std Dev	Minimum	Maximum
11	396.73	172.71	196	701
Censoring variable =No Group=Yes
Survival Time [Days]
N	Mean	Std Dev	Minimum	Maximum
5	429.2	138.35	250	578
Censoring variable =Yes Group=No
Survival Time [Days]
N	Mean	Std Dev	Minimum	Maximum
96	798.04	348.07	9	1246
Censoring variable =Yes Group=Yes
Survival Time [Days]
N	Mean	Std Dev	Minimum	Maximum
30	942.07	166.05	294	1141

As for the convergence, I don't get any errors/warnings. It says "convergence criteria satisfied"...

[JacobSimonsen]

It seems strange that the hazardratio should be that extreme. Can you attach the dataset? I would like to take a look on it.