Comorbidities Can Predict Mortality of Kidney Transplant Recipients: Comparison With the Charlson Comorbidity Index.

Abstract Background Comorbid conditions are important in the survival of kidney transplant recipients. The weights assigned to comorbidities to predict survival may vary based on the type of index disease and advances in the management of comorbidities. We aimed to develop a modified Charlson comorbidity index (CCI) in renal allograft recipients (mCCI-KT), thereby improving risk stratification for mortality. Methods A total of 3765 recipients in a multicenter cohort were included to develop a comorbidity score. The weights of the comorbidities, per the CCI, were recalibrated using a Cox proportional hazards model. Results Peripheral vascular disease, liver disease, myocardial infarction, and diabetes in the CCI were selected from the Cox proportional hazards model. Thus, the mCCI-KT included 4 comorbidities with recalibrated severity weights. Whereas the CCI did not discriminate for survival, the mCCI-KT provided significant discrimination for survival using the Kaplan-Meier method and Cox regression analysis. The mCCI-KT showed modest increases in c -statistics (0.54 vs 0.52, P  = .001) and improved net mortality risk reclassification by 16.3% (95% confidence interval, 3.2–29.4; P  = .015) relative to the CCI. Conclusion The mCCI-KT stratifies the risk for mortality in renal allograft recipients better than the CCI, suggesting that it may be a preferred index for use in clinical practice.