Hierarchical model for evaluating pyrantel efficacy against strongyle parasites in horses.

Anthelmintic resistance is an increasing challenge for the control of equine parasites. The fecal egg count reduction test (FECRT) is the practical gold standard method for evaluating reduction in anthelmintic efficacy, but the interpretation is complicated due to high levels of variability. A hierarchical statistical model was described for analysis of FECRT data from multiple farms to evaluate the role of biological factors in determining the strongyle efficacy of pyrantel pamoate in a study performed in Denmark. The model was then used to describe two notions of farm efficacy, namely conditional and marginal efficacy. The median of the lower prediction limits was used to describe a robust classification rule. The performance of the methodology was evaluated using Monte Carlo simulations. The field study was performed on 64 Danish horse farms of different breeds. Of 1644 horses, 614 had egg counts ≥ 200 eggs per gram (EPG) and were treated. Individual coprocultures were performed for identification of Strongylus vulgaris from all horses pre-treatment. Thirty-one farms (48.4%) were positive for S. vulgaris, but pyrantel efficacy was unaffected by the presence of this parasite in the statistical model. Further, there were no significant effects of age, gender, or interactions between these, while the pre-treatment egg count was negatively associated with the egg count reduction. The statistical model classified 81.3%, 10.9%, and 7.8% of farms as no signs of resistance (NR), suspect resistance (SR), and resistance (RE), respectively. In comparison, arithmetic calculations classified 68.8%, 17.2%, and 14.1% in the same categories. Using 10,000 simulated data sets, the methodology provided a classification of farms into different efficacy categories with a false discovery of reduced farm efficacy rate equaling 8.74%. In addition, model-classification was unaffected by presence of single outlier horses in a separate simulation study.

Statistical and biological considerations in evaluating drug efficacy in equine strongyle parasites using fecal egg count data.

Anthelmintic resistance (AR) is a serious problem for the control of equine gastrointestinal nematodes, particularly in the cyathostomins. The fecal egg count reduction test (FECRT) is the most common method for diagnosing AR and serves as the practical gold standard. However, accurate quantification of resistance and especially accurate diagnosis of emerging resistance to avermectin/milbemycin (A/M) drugs, is hampered by a lack of accepted standards for study design, data analysis, and data interpretation. In order to develop rational evidence-based standards for diagnosis of resistance, one must first take into account the numerous sources of variability, both biological and technical, that affect the measurement of fecal egg counts (FECs). Though usually ignored, these issues can greatly impact the observed efficacy. Thus, to accurately diagnose resistance on the basis of FECRT data, it is important to reduce levels of variability through improved study design, and then deal with inherent variability that cannot be removed, by performing thorough and proper statistical analysis. In this paper we discuss these issues in detail, and provide an explanation of the statistical models and methods that are most appropriate for analyzing these types of data. We also provide several examples using data from laboratory, field, and simulation experiments illustrating the benefits of these approaches.