17 Aug 2012 23:48

## REPOST: Need help interpreting output from rcorrp.cens with Cox regression

```I am reposting my message from April 8th because I never received a response to the original post:

Dear R-listers,

I am an MD and clinical epidemiologist developing a measure of comorbidity severity for patients with
liver disease. Having developed my comorbidity score as the linear predictor from a Cox regression model
I want to compare the discriminative ability of my comorbidity measure with the "old" comorbidity
measure, Charlson's Comorbidity Index. I have nearly 10,000 deaths and 36 candidate comorbidities.

I wish to compare the discrimination of the two comorbidity measures, i.e. I have two non-nested Cox
models. I get the following output with

> rcorrp.cens(myscore.lp, charlson.lp, Surv(time, dead), method=1):

x1 = My comorbidity score, x2 = Charlson
[,1]
Dxy                "-0.0605"
S.D.               "0.00648"
x1 more concordant "0.4697"
x2 more concordant "0.5302"
n                  "1.369e+04"
missing            "0"
uncensored         "9411"
Relevant Pairs     "1.587e+08"
Uncertain          "2.861e+07"
C X1               "0.395"
C X2               "0.401"
Dxy X1             "-0.21"
Dxy X2             "-0.198"

I am aware that because a high hazard means short survival I must subtract C X1 and C X2 from 1, so my
comorbidity score has marginally better discrimination than the Charlson score (C = 0.605 vs. 0.599).
Question: Is it true that my score is more discriminative than the Charlson score in 53% of patient pairs?

I have done the same analysis with 'method = 2', i.e.
> rcorrp.cens(myscore.lp, charlson.lp, Surv(time, dead), method=2):

x1 = My comorbidity score, x2 = Charlson
[,1]
Dxy                "-0.006002"
S.D.               "0.001102"
x1 more concordant "0.04018"
x2 more concordant "0.04618"
n                  "1.369e+04"
missing            "0"
uncensored         "9411"
Relevant Pairs     "1.587e+08"
Uncertain          "2.861e+07"
C X1               "0.395"
C X2               "0.401"
Dxy X1             "-0.21"
Dxy X2             "-0.198"

Question: How do I interpret the 'x1/x2 more concordant' numbers in a Cox regression setting? My guess: My
comorbidity score concordant in 4.6% of pairs in which Charlson's score is not. And Charlson's score is
concordant in 4.0% of pairs in which my comorbidity score is not.