Relapses in canine leishmaniosis: risk factors identified through mixed-effects logistic regression

Abstract

BackgroundCanine leishmaniosis (CanL), caused by Leishmania infantum, is an important vector-borne parasitic disease in dogs with implications for human health. Despite advancements, managing CanL remains challenging due to its complexity, especially in chronic, relapsing cases. Mathematical modeling has emerged as a powerful tool in various medical fields, but its application in understanding CanL relapses remains unexplored.MethodsThis retrospective study aimed to investigate risk factors associated with disease relapse in a cohort of dogs naturally infected with L. infantum. Data from 291 repeated measures of 54 dogs meeting the inclusion criteria were included. Two logistic mixed-effects models were created to identify clinicopathological variables associated with an increased risk of clinical relapses requiring a leishmanicidal treatment in CanL. A backward elimination approach was employed, starting with a full model comprising all potential predictors. Variables were iteratively eliminated on the basis of their impact on the model, considering both statistical significance and model complexity. All analyses were conducted using R software, primarily employing the lme4 package, and applying a significance level of 5% (P < 0.05).ResultsThis study identified clinicopathological variables associated with an increased risk of relapses requiring a leishmanicidal treatment. Model 1 revealed that for each 0.1 increase in the albumin/globulin ratio (A/G) ratio, the odds of requiring treatment decreased by 45%. Conversely, for each unit increase in the total clinical score (CS), the odds of requiring treatment increase by 22–30%. Indirect immunofluorescence antibody test (IFAT) was not a significant risk factor in model 1. Model 2, incorporating individual albumin and globulins values, showed that dogs with high IFAT titers, hyper beta-globulinemia, hypoalbuminemia, anemia, and high CS were at increased risk of relapse. Both models demonstrated a good fit and explained a substantial amount of variability in treatment decisions.ConclusionsDogs exhibiting higher CS, dysproteinemia, anemia, and high IFAT titers are at increased risk of requiring leishmanicidal treatment upon clinical relapse in CanL. Regular monitoring and assessment of risk factors prove essential for early detection of relapses and effective intervention in CanL cases. The contrasting findings between the two models highlight the complexity of aspects influencing treatment decisions in this disease and the importance of tailored management strategies to improve outcomes for affected dogs.Graphical