Statistical Evaluation of the Regulatory Guidelines for Use of Furosemide in Race Horses

Abstract

The pharmacokinetic behavior of furosemide concentrations in performance horses is of great interest to the equine industry and equine researchers. Specifically, such information is useful for the evaluation of the existing guidelines in several racing jurisdictions and for the possible development of new guidelines for varying time periods after administration. We studied several approaches within the framework of nonlinear mixed effects models to increase the accuracy of evaluating these guidelines. Theoretical properties of the proposed methods were examined and the variances of the resulting estimators compared. Their numerical performances were further evaluated through simulations. Finally, we applied these methods to a furosemide concentration profile data set and used our findings to address certain important practical issues.

Estimation of the probability for exceeding thresholds of urine specific gravity and plasma concentration of furosemide at various intervals after intravenous administration of furosemide in horses

“…9, September 2001 Using the previously described models in the first 2 equations with estimated coefficients calculated by use of the GTS algorithm, a semiparametric smooth functional averaging approach was used to estimate the probabilities of exceeding the threshold concentration over time for a specified dose of furosemide. 4 For purposes of this study, we selected a threshold of 100 ng of furosemide/ml and a urine specific gravity threshold of 1.012 at times between 4.0 and 5.5 hours after IV administration of the drug, because they reflected regulatory guidelines for some racetracks in North America. The preadministration observations were not used for modeling the urine specific gravity data, because modeling the initial response to furosemide was not of interest, and only limited data (0.5 hours before and 1 hour after administration of furosemide) were available to assess this initial response.…”

Density Deconvolution for Generalized Skew-Symmetric Distributions

“…Much of the GSS research has been theoretical in nature and while such theoretical work is important for understanding the statistical properties of GSS distributions, the applied value associated with this family of distributions has not often been realized in the literature. Notable and relevant exceptions that have used GSS distributions in application have considered the modeling of pharmacokinetic data, see Chu et al (2001), the redistribution of soil in tillage, see Van Oost et al (2003), and the retrospective analysis of case-control studies, see Guolo (2008). All of these authors considered only fully parametric models and therefore did not exploit the flexibility of GSS distributions as a semiparametric modeling tool.…”