Development and validation of a predictive mortality risk score from a European hemodialysis cohort

Abstract

Although mortality risk scores for chronic hemodialysis (HD) patients should have an important role in clinical decision-making, those currently available have limited applicability, robustness, and generalizability. Here we applied a modified Framingham Heart Study approach to derive 1- and 2-year all-cause mortality risk scores using a 11,508 European incident HD patient database (AROii) recruited between 2007 and 2009. This scoring model was validated externally using similar-sized Dialysis Outcomes and Practice Patterns Survey (DOPPS) data. For AROii, the observed 1- and 2-year mortality rates were 13.0 (95% confidence interval (CI; 12.3–13.8)) and 11.2 (10.4–12.1)/100 patient years, respectively. Increasing age, low body mass index, history of cardiovascular disease or cancer, and use of a vascular access catheter during baseline were consistent predictors of mortality. Among baseline laboratory markers, hemoglobin, ferritin, C-reactive protein, serum albumin, and creatinine predicted death within 1 and 2 years. When applied to the DOPPS population, the predictive risk score models were highly discriminatory, and generalizability remained high when restricted by incidence/prevalence and geographic location (C-statistics 0.68–0.79). This new model offers improved predictive power over age/comorbidity-based models and also predicted early mortality (C-statistic 0.71). Our new model delivers a robust and reproducible mortality risk score, based on readily available clinical and laboratory data.