Predictive performance of renal function equations in renal transplant recipients: an analysis of patient factors in bias - PubMed (original) (raw)
Predictive performance of renal function equations in renal transplant recipients: an analysis of patient factors in bias
Renate J Bosma et al. Am J Transplant. 2005 Sep.
Free article
Abstract
Creatinine-based equations are available to estimate GFR. After renal transplantation body composition usually changes, thus specific validation is required for transplant recipients. Nine equations were compared with iothalamate glomerular filtration rate (GFR) at 1 year after transplantation in 798 recipients. Equations were analyzed for precision, bias and accuracy. Sources of bias were analyzed by univariate and multivariate analysis, with body mass index (BMI), age and sex as independent variables and bias as dependent variable. Four hundred and seventy-eight patients were studied to assess whether the equations can be used to monitor renal function over time. Predictive performance was modest for all equations. MDRD and Jelliffe 2 were the best predictors of GFR. Bias was significantly related to BMI, age and gender in most equations. Multivariate analysis confirmed their independent contribution to the bias of MDRD, Jelliffe 2 and most other equations. Over time, bias was relatively stable at group level, but predictive performance in individuals was modest. The predictive performance of renal function equations is modest in renal transplants, which hampers their use for accurate assessment of renal function in the individual. The role of patient factors in the systematic error suggests that development of better equations should be feasible by better incorporation of these factors.
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