Model-Based Estimation of Iohexol Plasma Clearance for Pragmatic Renal Function Determination in the Renal Transplantation Setting

Abstract

Background: Iohexol plasma clearance-based glomerular filtration rate (GFR) determination provides an accurate method for renal function evaluation. This technique is increasingly advocated for clinical situations that dictate highly accurate renal function assessment, as an alternative to conventional serum creatinine-based methods with limited accuracy or poor feasibility. In the renal transplantation setting, this particularly applies to living renal transplant donor eligibility screening, renal transplant function monitoring and research purposes. The dependency of current iohexol GFR estimation techniques on extensive sampling, however, has limited its clinical application. We developed a population pharmacokinetic model and limited sampling schedules, implemented in the online InsightRX precision dosing platform, to facilitate pragmatic iohexol GFR assessment.

Methods: Iohexol concentrations (n = 587) drawn 5 min to 4 h after administration were available from 67 renal transplant recipients and 41 living renal transplant donor candidates with measured iohexol GFRs of 27-117 mL/min/1.73 m². These were split into a model development (n = 72) cohort and an internal validation (n = 36) cohort. External validation was performed with 1040 iohexol concentrations from 268 renal transplant recipients drawn between 5 min and 4 h after administration, and extended iohexol curves up to 24 h from 11 random patients with impaired renal function. Limited sampling schedules based on one to four blood draws within 4 h after iohexol administration were evaluated in terms of bias and imprecision, using the mean relative prediction error and mean absolute relative prediction error. The total deviation index and percentage of limited sampling schedule-based GFR predictions within ± 10% of those of the full model (P₁₀) were assessed to aid interpretation.

Results: Iohexol pharmacokinetics was best described with a two-compartmental first-order elimination model, allometrically scaled to fat-free mass, with patient type as a covariate on clearance and the central distribution volume. Model validity was confirmed during the internal and external validation. Various limited sampling schedules based on three to four blood draws within 4 h showed excellent predictive performance (mean relative prediction error < ± 0.5%, mean absolute relative prediction error < 3.5%, total deviation index < 5.5%, P₁₀ > 97%). The best limited sampling schedules based on three to four blood draws within 3 h showed reduced predictive performance (mean relative prediction error < ± 0.75%, mean absolute relative prediction error < 5.5%, total deviation index < 9.5%, P₁₀ ≥ 85%), but may be considered for their enhanced clinical feasibility when deemed justified.

Conclusions: Our online pharmacometric tool provides an accurate, pragmatic, and ready-to-use technique for measured GFR-based renal function evaluation for clinical situations where conventional methods lack accuracy or show limited feasibility. Additional adaptation and validation of our model and limited sampling schedules for renal transplant recipients with GFRs below 30 mL/min is warranted before considering this technique in these patients.

Fig. 1

Diagnostic plots for the final population pharmacokinetic model on the development cohort. a Observed vs individual predicted iohexol concentrations. b Conditional weighted residuals (CWRES) vs individual predicted iohexol concentrations. c Observed vs population predicted iohexol concentrations. d Conditional weighted residuals (CWRES) vs time after iohexol administration. The solid gold lines and gold-shaded areas in a–d represent the local weighted (loess) regression fit and the standard error around the loess regression fit. e Prediction-corrected visual predictive check (VPC), in which the solid black lines represent the 5th, 50th, and 95th percentiles of the observed iohexol concentrations and the dashed gold lines and gold-shaded areas depict the 5th, 50th, and 95th percentiles of the model-simulated iohexol concentrations and their respective 95% confidence intervals

Fig. 2

Prediction-corrected visual predictive checks and individual prediction diagnostic plots for the a, b internal validation cohort and c, d external validation cohort. The solid black lines in a and c represent the 5th, 50th, and 95th percentiles of the observed iohexol concentrations and the dashed purple and blue lines and purple- and blue-shaded areas depict the 5th, 50th, and 95th percentiles of the model-simulated iohexol concentrations and their respective 95% confidence intervals. The solid purple and blue lines and purple- and blue-shaded areas in b and d represent the local weighted (loess) regression fit and the standard error around the loess regression fit

Fig. 3

Limited sampling schedule selection. a Individual iohexol clearance prediction bias of all limited sampling schedules, sorted according to the median bias and the number of sampling instances. b Individual iohexol clearance prediction imprecision, sorted according to the median imprecision and the number of sampling instances. Each boxplot represents the data of a 1000 simulated individuals. Limited sampling schedules that showed a total deviation index (TDI) below 10% and below 5%, indicating good and excellent predictive performance, are highlighted in gold and red, respectively

Fig. 4

Predictive performances of selected limited sampling schedules (LSSs). a Scatter and b Bland–Altman ratio plots of the reference (GFR_full) and predicted iohexol clearance (GFR_lss). The best LSSs based on three to four samples within 3 h are depicted in gold, whereas the two LSSs with particular clinical interest are depicted in purple. The best LSSs based on three to four samples within 4 h are indicated in blue. Solid gold, purple, and blue lines and gold-, purple-, and blue-shaded areas represent the loess regression fits and their standard errors. The solid and upper and lower dashed black lines represent the mean ratios, upper limits of agreement (LoA) and lower LoA. Solid grey lines represent the lines of equality