Prediction of measured GFR after living kidney donation from pre-donation parameters

BACKGROUND: One of the challenges in living kidney donor screening is to estimate remaining kidney function after donation. Here we developed a new model to predict post-donation measured glomerular filtration rate (mGFR) from pre-donation serum creatinine, age and sex. METHODS: In the prospective development cohort (TransplantLines, n = 511), several prediction models were constructed and tested for accuracy, precision and predictive capacity for short- and long-term post-donation (125)I-iothalamate mGFR. The model with optimal performance was further tested in specific high-risk subgroups (pre-donation eGFR <90 mL/min/1.73 m(2), a declining 5-year post-donation mGFR slope or age >65 years) and validated in internal (n = 509) and external (Mayo Clinic, n = 1087) cohorts. RESULTS: In the development cohort, pre-donation estimated GFR (eGFR) was 86 ± 14 mL/min/1.73 m(2) and post-donation mGFR was 64 ± 11 mL/min/1.73 m(2). Donors with a pre-donation eGFR ≥90 mL/min/1.73 m(2) (present in 43%) had a mean post-donation mGFR of 69 ± 10 mL/min/1.73 m(2) and 5% of these donors reached an mGFR <55 mL/min/1.73 m(2). A model using pre-donation serum creatinine, age and sex performed optimally, predicting mGFR with good accuracy (mean bias 2.56 mL/min/1.73 m(2), R(2) = 0.29, root mean square error = 11.61) and precision [bias interquartile range (IQR) 14 mL/min/1.73 m(2)] in the external validation cohort. This model also performed well in donors with pre-donation eGFR <90 mL/min/1.73 m(2) [bias 0.35 mL/min/1.73 m(2) (IQR 10)], in donors with a negative post-donation mGFR slope [bias 4.75 mL/min/1.73 m(2) (IQR 13)] and in donors >65 years of age [bias 0.003 mL/min/1.73 m(2) (IQR 9)]. CONCLUSIONS: We developed a novel post-donation mGFR prediction model based on pre-donation serum creatinine, age and sex.