A Novel Risk Score for Mortality in Renal Transplant Recipients Beyond the First Posttransplant Year

Abstract

Background. All-cause mortality is high after kidney transplantation (KT), but no prognostic index has focused on predicting mortality in KT using baseline and emergent comorbidity after KT. Methods. A total of 4928 KT recipients were used to derive a risk score predicting mortality. Patients were randomly assigned to two groups: a modeling population (n=2452), used to create a new index, and a testing population (n=2476), used to test this index. Multivariate Cox regression model coefficients of baseline (age, weight, time on dialysis, diabetes, hepatitis C, and delayed graft function) and emergent comorbidity within the first posttransplant year (diabetes, proteinuria, renal function, and immunosuppressants) were used to weigh each variable in the calculation of the score and allocated into risk quartiles. Results. The probability of death at 3 years, estimated by baseline cumulative hazard function from the Cox model [P (death)=1−0.993592764exp(score/100)], increased from 0.9% in the lowest-risk quartile (score=40) to 4.7% in the highest risk-quartile (score=200). The observed incidence of death increased with increasing risk quartiles in testing population (log-rank analysis, P<0.0001). The overall C-index was 0.75 (95% confidence interval: 0.72–0.78) and 0.74 (95% confidence interval: 0.70–0.77) in both populations, respectively. Conclusion. This new index is an accurate tool to identify high-risk patients for mortality after KT.