APPLICATION OF INDIVIDUALIZED BAYESIAN UREA KINETIC MODELING TO PEDIATRIC HEMODIALYSIS

Olivera Marsenic, Athena Zuppa, Jeffrey S. Barrett, Marc Pfister

Laboratory for Applied PK/PD, Division of Clinical Pharmacology and Therapeutics and Division of Nephrology, The Children's Hospital of Philadelphia; Philadelphia, PA

NAPRTCS data show that 2252 children younger than 19 years have received maintenance hemodialysis (HD) in the USA in 2007. They comprise 36% of all pediatric dialysis patients. Urea kinetic modeling (UKM) is used to quantify and prescribe HD treatment.

UKM results are expressed as K (urea clearance) * t (time) / V (urea distribution volume), PCR (protein catabolic rate), URR (urea reduction ratio) Kt/V, PCR AND URR are dependant on accuracy of urea measurements If end-HD urea is used single pool Kt/V and UKM If 60-min post-HD urea is used double pool Kt/V and UKM Ceq (equilibrated urea concentration) is impractical to obtain in the clinical setting Model that predicts Ceq using BUN measurements during or right after HD can improve HD therapy for children.

We used IBUKM in pediatric HD patients, to assess its ability to predict Ceq in childrenRetrospective data:

Marsenic O et al: Comparison of two methods for predicting equilibrated Kt/V (eKt/V) using true eKt/V value.Pediatr Nephrol. 1999 Jun;13(5):418-22.

Patients: 30 HD sessions in 13 children (M:7, F:6) (7 pts x 3, 1 pt x 2, 7 pts x 1 HD session) age 14.6+2.2 years; weight 35.6+9.6 kg

Blood sampling: pre HD 70 min into HD (C70) end of HD (Ct) 60 min after the end of HD (Ceq)

Patient groups: Group A: included C70 Group B: did not include C70

Statistical analysis: Paired t-test; Pearson correlation Percent bias of predicted Ceq = [(estimated - measured) /measured]*100

INDIVIDUALIZED BAYESIAN UREA KINETIC MODELING Pfister et al, A new Bayesian method to forecast and fine tune individual hemodialysis

dose, Hemodialysis International 2004; 8: 224-256

To apply Individualized Bayesian Urea Kinetic Modeling, designed for adults, to pediatric hemodialysis and assess its performance and accuracy in children on chronic hemodialysis

BACKGROUND

OBJECTIVES

RESULTS

METHODS

CONCLUSIONS We provide initial results of IBUKM strategy to predict Ceq in pediatric patients. This method predicts Ceq for an HD session using pre and post HD BUN values for that session, with minimal

bias. C70 BUN does not improve Ceq predictions Future model development:

forecasting individual Ceq from previous sessions evaluate the impact of covariates specific for children account for inter-occasion variability

IBUKM will account for time-dependent changes in pediatric patient characteristics and HD By accurate quantification of HD in children, optimal HD delivery can be achieved. This will result in decreased

morbidity and improved growth and development while on HD.

Urea values (mmol/l), true vs. IBUKM predicted

true group A group B

Ct 8.0±3.5

Ceq 9.5±3.8 9.6±3.9 9.4±3.8

UR 19.7±10%

IBUKM predicted values vs. true values

group A group B

T-test NS NS

Correlation 0.984 0.977

Percent bias* 5.6±4.8% 6.2±4.4%

*T-test for A vs B error is NS

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Graph 1: Ct vs true Ceq (mmol/l) (Ct=blue diamonds, C60=pink squares)

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Graph 2: Group A Ceq (mmol/l) prediction by IBUKM

Graph 4: Group B Ceq (mmol/l) prediction by IBUKM

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Graph 3: Group A % error of IBUKM prediction

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Graph 5: Group B % error of IBUKM prediction

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UREA REBOUND (UR) AFTER HEMODIALYSIS (HD) Urea concentration in plasma increases (rebounds) after HD as expression of interpool

(intracellular fluid (ICF) to extracellular fluid (ECF)) reequilibration. Urea rebound (UR) is completed 1 hour after HD UR is more pronounced in children, and is caused by: 1) Mass transfer resistance of the

biological membranes; 2) Rapid removal of solutes from plasma during HD: relatively higher efficiency of HD in children (urea distribution volume is smaller than in adults); 3) Variations in regional blood flow

HD efficiency in children is best assessed with incorporation of UR

INDIVIDUALIZED BAYESIAN UREA KINETIC MODELING (IBUKM): IBUKM is based on a two-pool urea kinetic model and accounts for HD prescription

parameters, using Bayesian individualization with NONMEM® software Bayesian statistical network is used so that prior knowledge of population urea kinetics is used

with current and historic individual BUN kinetic data to arrive at predictions of individual dialysis response

IBUKM is used to assess effects of various dialysis settings on urea kinetics and to forecast and fine-tune treatment parameters of future HD sessions

IBUKM may be applied to non-urea solutes with specific clearance characteristicsIBUKM development

Model was built from data from 18 adult patients and their 38 HD sessions The population distribution of urea kinetic parameters was derived from the 18 pts, and

individual urea kinetic data were used to make individual predictions IBUKM estimates of Ceq were compared to measured Ceq at 30 min post-HD The error in predicting Ceq was within the urea measurement error itself

Graphs 1-5:

Graph 1 is showing degree of urea rebound with Ct and Ceq presented together for each HD session

Graph 2 and Graph 4 are showing high correlation of true and predicted Ceq.

Graph 3 and Graph 5 are showing that the error in predicting Ceq is randomly distributed and that there is no systematic trend in error.