Search

To evaluate by simulation the statistical properties of normalized prediction distribution errors (NPDE), prediction discrepancies (pd), standardized prediction errors (SPE), numerical predictive check (NPC) and decorrelated NPC (NPC(dec)) for the external evaluation of a population pharmacokinetic analysis, and to illustrate the use of NPDE for the evaluation of covariate models. We assume that a model M(B) has been built using a building dataset B, and that a separate validation dataset, V is available. Our null hypothesis H(0) is that the data in V can be described by M(B). We use several methods to test this hypothesis: NPDE, pd, SPE, NPC and NPC(dec). First, we evaluated by simulation the type I error under H(0) of different tests applied to the four methods. We also propose and evaluate a single global test combining normality, mean and variance tests applied to NPDE, pd and SPE. We perform tests on NPC and NPC(dec), after a decorrelation. M(B) was a one compartment model with first order absorption (without covariate), previously developed from two phase II and one phase III studies of the antidiabetic drug, gliclazide. We simulated 500 external datasets according to the design of a phase III study. Second, we investigated the application of NPDE to covariate models. We propose two approaches: the first approach uses correlation tests or mean comparisons to test the relationship between NPDE and covariates; the second evaluates NPDE split by category for discrete covariates or quantiles for continuous covariates. We generated several validation datasets under H(0) and under alternative assumptions with a model without covariate, with one continuous covariate (weight), or one categorical covariate (sex). We calculated the powers of the different tests using simulations, where the covariates of the phase III study were used. The simulations under H(0) show a high type I error for the different tests applied to SPE and an increased type I error for pd. The different tests present a type I error close to 5% for the global test appied to NPDE. We find a type I error higher than 5% for the test applied to classical NPC but this test becomes close to 5% for NPC(dec). For covariate models, when model and validation dataset are consistent, type I error of the tests are close to 5% for both effects. When validation datasets and models are not consistent, the tests detect the correlation between NPDE and the covariate. We recommend to use NPDE over SPE for external model evaluation, since they do not depend on an approximation of the model and have good statistical properties. NPDE represent a better approach than NPC, since in order to perform tests on NPC, a decorrelation step must be applied before. NPDE, in this illustration, is also a good tool to evaluate model with or without covariates.

The aminoglycoside gentamicin is often used in equine practice. Despite its clinical use, concerns remain regarding the potential toxic side-effects, such as nephrotoxicity, in equine patients, particularly after repeated dosing. The aim of the study was to investigate first in vitro the mechanisms contributing to the renal toxicity of gentamicin and to identify sensitive biomarkers indicating proximal tubule damage. To this end, the kidney-derived cell lines LLC-PKI and MDCK were treated with gentamicin at different concentrations. Toxicity was assessed by measuring the release of gamma-glutamyl transferase (GGT), and the production of reactive oxygen species (ROS). Cell viability was measured using Alamar blue (AB) and Neutral red (NR) cytotoxicity assays. Gentamicin exerted a dose-dependent toxicity. Primarily, loss of brush border membrane integrity, indicated by GGT leakage, and an increased ROS production were observed. As GGT was found to be a sensitive marker for gentamicin-induced renal cell injury, in the subsequent in vivo experiments, in which ponies were given gentamicin (3.0 mg/kg bw three times daily and 4.5 mg/kg bw twice daily) for five consecutive days, plasma levels and the urinary excretion of GGT and creatinine were measured and the GGT:creatinine ratio was calculated. Elevated GGT levels in urine following gentamicin therapy were observed, but this enzyme leakage was transient and returned to baseline values after cessation of therapy. It could thus be concluded that even a conservative dose regimen of gentamicin did not result in significant renal toxicity in healthy ponies.

The aminoglycoside antibiotic gentamicin is commonly used in equine medicine for the prevention and treatment of Gram-negative and staphylococcal bacteria in surgically treated colic patients. The pharmacokinetics of gentamicin in these patients might be altered by the disease status, and/or under the influence of fluid therapy. The purpose of this study was to investigate the effect of intravenous fluid treatment on gentamicin kinetics in colic patients. Colic patients subjected to laparotomy were given fluid infusions according to clinical status. Following gentamicin administration, blood samples were taken for gentamicin analysis at different time points, and the main pharmacokinetic parameters including Vc, Vss, t(1/2) and MRT were calculated. Horses undergoing fluid therapy showed a significantly different t(1/2), clearance and MRT as compared to non-infused patients. However, taking into account the clinical status of the patients receiving fluid support, the data suggest that endotoxaemia, rather than fluid therapy, influence gentamicin pharmacokinetics following laparotomy.

Several bacterial and viral agents have been implicated in the pathogenesis of the Guillain-Barré syndrome, an acquired immune-mediated disorder. A case of Guillain-Barré syndrome associated with acute Q fever is described. Coxiella burnetii should therefore be added to the list of microorganisms capable of inducing the Guillain-Barré syndrome.