Predicting Mortality in Incident Dialysis Patients: An Analysis of the United Kingdom Renal Registry - Wagner, Martin (2011)
BACKGROUND: The risk of death in dialysis patients remains high, but varies significantly among patients. No prediction tool is widely used in current clinical practice. We aimed to predict long-term mortality in incident dialysis patients with easily obtainable variables. STUDY DESIGN: Prospective nationwide multicenter cohort study in the United Kingdom (UK Renal Registry); Models were developed using Cox proportional hazards. SETTING AND PARTICIPANTS: Patients initiating hemodialysis or peritoneal dialysis between 2002 and 2004, who survived at least three months on dialysis treatment, were followed for three years. Analyses were restricted to subjects in whom information on comorbid conditions and laboratory measurements were available (n=5447). The dataset was divided into datasets for model development (n=3631, training) and validation (n=1816) by random selection. PREDICTORS: Basic patient characteristics, comorbidity and laboratory variables. OUTCOMES: All cause mortality censored for kidney transplant, recovery of kidney function, and loss to follow-up. RESULTS: In the training dataset, 1078 patients (29.7%) died within the observation period. The final model of the training dataset included patient characteristics (age, race, primary kidney disease, treatment modality), comorbidities (diabetes, history of cardiovascular disease, smoking) and laboratory variables (hemoglobin, serum albumin, creatinine, calcium) and reached a C-statistic of 0.75 (95% CI, 0.73–0.77) and could accurately discriminate between patients with low (6%), intermediate (19%), high (33%) and very high (59%) mortality risk. The model was further applied to the validation dataset and achieved a C-statistic of 0.73 (95% CI, 0.71–0.76). LIMITATIONS: Number of missing comorbidity data and lack of an external validation dataset. CONCLUSIONS: Basic patient characteristics, comorbidity and laboratory variables can predict three-year mortality in incident dialysis patients with sufficient accuracy. Identification of subgroups of patients according to mortality risk can guide future research and subsequently target treatment decisions in individual patients.