Predicting potential survival benefit of renal transplantation in patients with chronic kidney disease

Background: To facilitate decision-making about treatment options for patients with end-stage renal disease considering kidney transplantation, we sought to develop an index for clinical prediction of risk for death. Methods: We derived and validated a multivariable survival model predicting time to death in 169 393 patients with end-stage renal disease who were eligible for transplantation. We modified the model into a simple point-system index. Results: Deaths occurred in 23.5% of the cohort. Twelve variables independently predicted death: age, race, cause of kidney failure, body mass index, comorbid disease, smoking, employment status, serum albumin level, year of first renal replacement therapy, kidney transplantation, time to transplant wait-listing and time on the wait list. The index separated patients into 26 groups having significantly unique five-year survival, ranging from 97.8% in the lowest-risk group to 24.7% in the highest-risk group. The index score was discriminative, with a concordance probability of 0.746 (95% CI 0.741-0.751). Observed survival in the derivation and validation cohorts was similar for each level of index score in 93.9% of patients. Interpretation: Our prognostic index uses commonly available information to predict mortality accurately in patients with end-stage renal disease. This index could provide valuable quantitative data on survival for clinicians and patients to use when deciding whether to pursue transplantation or remain on dialysis.