Bayesian estimation of p-aminohippurate clearance by a limited sampling strategy

This study describes a methodology to calculated p-aminohippurate (PAH) clearance (CL) and volume of distribution (V) with both the population parameters and one or two samples taken during the disposition and the elimination phase after a single intravenous infusion. The computer program P-PHARM was used, and a log-normal distribution and a heteroscedastic residual error distribution were assumed. Ninety-six patients with and without renal insufficiency were available for analysis, and a two-compartment model was used for data modeling. Population parameters were evaluated for 70 patients (mean number of observed concentration per individual, 6) by a three-step approach. In step 1, the computer program was used to estimate the average pharmacokinetic parameters without taking into account the demographic and/or biological factors. In step 2, the relationship between the posterior individual estimates and the covariables was investigated with multiple linear stepwise algorithm. In step 3, the population parameters were re-estimated considering the relationship with the covariables. From the regression performed in step 2, the following covariables were included: serum creatinine, body surface area, and body weight. The population averages of CL and V were 30.7 +/- 2.36 L/h and 10.6 +/- 1.29 L, respectively. To evaluate the predictive performance of the population parameters, the remaining 26 patients were used. The population parameters combined with one or two individual PAH plasma concentrations led to a bayesian estimation of individual CL and V. This estimation was compared with the classical procedure of parameter estimation (individual fitting from multiple blood samples).(ABSTRACT TRUNCATED AT 250 WORDS)