Background: In dialysis patients with anemia, avoiding red blood cell transfusions is preferable. We sought to develop and validate a novel transfusion prediction risk score for patients receiving maintenance hemodialysis. Methods: This retrospective cohort study used United States Renal Data System data to create a model development cohort (point prevalent hemodialysis patients on November 1, 2012) and a validation cohort (point prevalent hemodialysis patients on August 1, 2013). We characterized comorbidity, inflammatory conditions, hospitalizations, anemia and anemia management, iron parameters, intravenous iron use, and vitamin D use during a 6-month baseline period to predict subsequent 3-month transfusion risk. We used logistic least absolute shrinkage and selection operator regression. In an exploratory analysis, model results were used to calculate a score to predict 6- and 12-month hospitalization and mortality. Results: Variables most predictive of transfusion were prior transfusion, hemoglobin, ferritin, and number of hospital days in the baseline period. The resulting C-statistic in the validation cohort was 0.74, indicating relatively good predictive power. The score was associated with a significantly increased risk of subsequent mortality (hazard ratios 1.0, 1.22, 1.26, 1.54, 1.71 grouped from lowest to highest score), but not with hospitalization. Conclusions: We developed a transfusion prediction risk score with good performance characteristics that was associated with mortality. This score could be further developed into a clinically useful application allowing clinicians to identify hemodialysis patients most likely to benefit from a timely, proactive anemia treatment approach with the goal of avoiding red blood cell transfusions and attendant risks of adverse clinical outcomes.
The association of red blood cell parameters with mortality in a population of hemodialysis patients