New Statistical Model to Evaluate Dewormer Efficacy

Research teams from the University of Kentucky Gluck Equine Research Center and George Mason University have defined a new advanced statistical model to evaluate anthelmintic dewormer efficacy.
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Research teams from the University of Kentucky Gluck Equine Research Center and George Mason University have defined a new advanced statistical model to evaluate anthelmintic dewormer efficacy. The researchers set out to illustrate sources of variability in fecal egg count reduction tests in horses and to develop a model to identify biological factors such as age, gender, and farm management that affect dewormer efficacy.

Fecal egg count reduction tests to evaluate dewormer efficacy is the most common method to determine drug resistance to horse parasites. In cases where the efficacy is either very high or very low, there are few statistical challenges to consider, and results are often clear without complicated data analysis.

Martin Nielsen, DVM, PhD, Dipl. EVPC, ACVM, assistant professor at the Gluck Center, said when results are close to the chosen cutoff value for determining resistance, the variability plays an important role and can lead to misclassification of some farms.

“The statistical model we have developed accounts for various biological sources of egg count variability and provides a more reliable result,” he said. “We chose to study the efficacy of pyrantel pamoate (a commonly used dewormer). Efficacy data generated with this drug is known to have a great deal of variability. The overall aim of the study is to differentiate between a true egg count reduction and an apparent reduction due to chance variability in the data

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