Peter Jepsen
2012-Apr-08 08:19 UTC
[R] Need help interpreting output from rcorrp.cens with Cox regression
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; with correction for optimism bias using the rms package my model's C falls to 0.602). 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 but Charlson's score is not. And Charlson's score is concordant in 4.0% of pairs but my comorbidity score is not. Thank you in advance for your insight and help. Best regards, Peter Jepsen Aarhus, Denmark [[alternative HTML version deleted]]