PROC PHREG - issues with CLASS statement

[Thuva]

I am trying to run an unadjusted model with a categorical variable. The survival model is a shared frailty model with recurrent events. What I need is an overall hazard ratio and 95% CI for the categorical variable (across all individuals), however I am getting a hazard ratio for each individual. 

The categorical variables I am interested in are all binary (0=no history disease, 1=yes history of disease), can I just remove the CLASS statement and add them as a continuous variable in the model?

My code:

proc phreg data=final_survival_export covs(aggregate) covm; 
class pt_id /*need this to specify ID variable for random effect*/
         prev_corticosteroids (ref='0'); /*character variable of interest*/
model (visit0 visit1)*rs(0)= prev_corticosteroids/rl;
random pt_id /NOCLPRINT ;
run;

My output for prev_corticosteroids is per individual, however I would like an aggregate estimate. Any help would be greatly appreciated!! 

SAS Output

Parameter		DF	Parameter Estimate	Standard Error	Chi-Square	Pr > ChiSq	Hazard Ratio	Label
prev_corticosteroids	1	1	0.13427	0.08226	2.6640	0.1026	1.144	prev_corticosteroids 1
prev_corticosteroids	2	1	0.57236	0.37623	2.3144	0.1282	1.772	prev_corticosteroids 2
prev_corticosteroids	3	1	0.75211	0.29420	6.5356	0.0106	2.121	prev_corticosteroids 3
prev_corticosteroids	4	1	0.70392	0.45005	2.4464	0.1178	2.022	prev_corticosteroids 4
prev_corticosteroids	5	1	0.68733	0.42074	2.6688	0.1023	1.988	prev_corticosteroids 5
prev_corticosteroids	6	1	0.65960	0.54052	1.4891	0.2224	1.934	prev_corticosteroids 6
prev_corticosteroids	7	1	0.64128	0.76435	0.7039	0.4015	1.899	prev_corticosteroids 7
prev_corticosteroids	8	1	0.62440	1.06027	0.3468	0.5559	1.867	prev_corticosteroids 8
prev_corticosteroids	9	1	0.66906	0.74098	0.8153	0.3666	1.952	prev_corticosteroids 9
prev_corticosteroids	11	1	0.60798	0.73777	0.6791	0.4099	1.837	prev_corticosteroids 11
prev_corticosteroids	12	1	0.59177	0.73702	0.6447	0.4220	1.807	prev_corticosteroids 12
prev_corticosteroids	13	1	0.69821	0.73636	0.8991	0.3430	2.010	prev_corticosteroids 13
prev_corticosteroids	14	1	0.61152	0.60854	1.0098	0.3149	1.843	prev_corticosteroids 14
prev_corticosteroids	15	1	0.61313	1.03611	0.3502	0.5540	1.846	prev_corticosteroids 15
prev_corticosteroids	18	1	0.62734	1.03652	0.3663	0.5450	1.873	prev_corticosteroids 18
prev_corticosteroids	19	1	0.62636	1.04223	0.3612	0.5479	1.871	prev_corticosteroids 19
prev_corticosteroids	24	1	0.64995	1.02797	0.3998	0.5272	1.915	prev_corticosteroids 24
prev_corticosteroids	29	1	0.66863	1.02493	0.4256	0.5142	1.952	prev_corticosteroids 29

[Reeza]

I’m not familiar with that particular model, but did you try a HazardRatio statement?

[JacobSimonsen · Accepted solution]

when all your covariates are binary (0,1) variables, then you can add them as continous variables. The estimates will show diffrence between the "1" and "0".

You can also use the class variable, as you already did. So cant see what you do wrong. Are yo sure that the prev_corticosteroids is binary. For me it looks like it contains the number of previous events in the recurrent event model.

[Thuva]

Can't believe I missed that! You are absolutely correct - I had two continuous variables that should not have been classified as categorical variables. Thanks for your help!