In contrast to European countries, the overwhelming majority of dogs in the U.S. are neutered (including spaying), usually done before one year of age. Given the importance of gonadal hormones in growth and development, this cultural contrast invites an analysis of the multiple organ systems that may be adversely affected by neutering. Using a single breed-specific dataset, the objective was to examine the variables of gender and age at the time of neutering versus leaving dogs gonadally intact, on all diseases occurring with sufficient frequency for statistical analyses. Given its popularity and vulnerability to various cancers and joint disorders, the Golden Retriever was chosen for this study. Veterinary hospital records of 759 client-owned, intact and neutered female and male dogs, 1–8 years old, were examined for diagnoses of hip dysplasia (HD), cranial cruciate ligament tear (CCL), lymphosarcoma (LSA), hemangiosarcoma (HSA), and mast cell tumor (MCT). Patients were classified as intact, or neutered early (<12 mo) or late (≥12 mo). Statistical analyses involved survival analyses and incidence rate comparisons. Outcomes at the 5 percent level of significance are reported. Of early-neutered males, 10 percent were diagnosed with HD, double the occurrence in intact males. There were no cases of CCL diagnosed in intact males or females, but in early-neutered males and females the occurrences were 5 percent and 8 percent, respectively. Almost 10 percent of early-neutered males were diagnosed with LSA, 3 times more than intact males. The percentage of HSA cases in late-neutered females (about 8 percent) was 4 times more than intact and early-neutered females. There were no cases of MCT in intact females, but the occurrence was nearly 6 percent in late-neutered females. The results have health implications for Golden Retriever companion and service dogs, and for oncologists using dogs as models of cancers that occur in humans.
Four covariate selection approaches were compared: a directed acyclic graph (DAG) full model and 3 DAG and change-in-estimate combined procedures. Twenty-five scenarios with case-control samples were generated from 10 simulated populations in order to address the performance of these covariate selection procedures in the presence of confounders of various strengths and under DAG misspecification with omission of confounders or inclusion of nonconfounders. Performance was evaluated by standard error, bias, square root of the mean-squared error, and 95% confidence interval coverage. In most scenarios, the DAG full model without further covariate selection performed as well as or better than the other procedures when the DAGs were correctly specified, as well as when confounders were omitted. Model reduction by using change-in-estimate procedures showed potential gains in precision when the DAGs included nonconfounders, but underestimation of regression-based standard error might cause reduction in 95% confidence interval coverage. For modeling binary outcomes in a case-control study, the authors recommend construction of a "conservative" DAG, determination of all potential confounders, and then change-in-estimate procedures to simplify this full model. The authors advocate that, under the conditions investigated, the selection of final model should be based on changes in precision: Adopt the reduced model if its standard error (derived from logistic regression) is substantially smaller; otherwise, the full DAG-based model is appropriate.
Although frequentist approaches to prevalence estimation are simple to apply, there are circumstances where it is difficult to satisfy assumptions of asymptotic normality and nonsensical point estimates (greater than 1 or less than 0) may result. This is particularly true when sample sizes are small, test prevalences are low and imperfect sensitivity and specificity of diagnostic tests need to be incorporated into calculations of true prevalence. Bayesian approaches offer several advantages including direct computation of range-respecting interval estimates (e.g. intervals between 0 and 1 for prevalence) without the requirement of transformations or large-sample approximations, direct probabilistic interpretation, and the flexibility to model in a straightforward manner the probability of zero prevalence. In this review, we present frequentist and Bayesian methods for animal- and herd-level true prevalence estimation based on individual and pooled samples. We provide statistical methods for detecting differences between population prevalence and frequentist methods for sample size and power calculations. All examples are motivated using Mycobacterium avium subspecies paratuberculosis infection and we provide WinBUGS code for all examples of Bayesian estimation.
A field trial was conducted to investigate the impact of oral vaccination of free-living badgers against natural-transmitted Mycobacterium bovis infection. For a period of three years badgers were captured over seven sweeps in three zones and assigned for oral vaccination with a lipid-encapsulated BCG vaccine (Liporale-BCG) or with placebo. Badgers enrolled in Zone A were administered placebo while all badgers enrolled in Zone C were vaccinated with BCG. Badgers enrolled in the middle area, Zone B, were randomly assigned 50:50 for treatment with vaccine or placebo. Treatment in each zone remained blinded until the end of the study period. The outcome of interest was incident cases of tuberculosis measured as time to seroconversion events using the BrockTB Stat-Pak lateral flow serology test, supplemented with post-mortem examination. Among the vaccinated badgers that seroconverted, the median time to seroconversion (413 days) was significantly longer (p = 0.04) when compared with non-vaccinated animals (230 days). Survival analysis (modelling time to seroconversion) revealed that there was a significant difference in the rate of seroconversion between vaccinated and non-vaccinated badgers in Zones A and C throughout the trial period (p = 0.015). For badgers enrolled during sweeps 1–2 the Vaccine Efficacy (VE) determined from hazard rate ratios was 36% (95% CI: -62%– 75%). For badgers enrolled in these zones during sweeps 3–6, the VE was 84% (95% CI: 29%– 97%). This indicated that VE increased with the level of vaccine coverage. Post-mortem examination of badgers at the end of the trial also revealed a significant difference in the proportion of animals presenting with M. bovis culture confirmed lesions in vaccinated Zone C (9%) compared with non-vaccinated Zone A (26%). These results demonstrate that oral BCG vaccination confers protection to badgers and could be used to reduce incident rates in tuberculosis-infected populations of badgers.
Data from 3 commercial rendering companies located in different regions of California were analyzed from September 2003 through August 2005 to examine the relationship of dairy calf and cow mortality to monthly average daily temperature and total monthly precipitation respectively. Yearly average mortality varied between rendering regions from 2.1 to 8.1% for mature cows. The relationship between cow and calf monthly mortality and monthly average daily temperature was U-shaped. Overall, months with average daily temperatures less than 14 and greater than 24 degrees C showed substantial increases in both calf and cow mortality with calf mortality being more sensitive to changes in these temperature ranges than cow mortality. Temperature changes were reflected in a 2-fold difference between the minimum and maximum mortality in cows and calves. Precipitation showed a weak effect with calf mortality and no effect with cow mortality. Data from Dairy Herd Improvement Association were used from 112 California herds tested over a 24-mo period to examine the relationship of milk production and quality with monthly average daily temperature and monthly precipitation. Somatic cell count and percent milk fat were either weakly or not associated with monthly average daily temperature and total monthly precipitation. However, total monthly precipitation was negatively associated with test day milk per milking cow regardless of the dairy's geographical location. Housing-specific associations for test day milk per milking cow were greater for total monthly precipitation than monthly average daily temperature, with the strongest negative association seen for dairies that do not provide shelter for cows. This suggests that providing suitable housing for lactating dairy cattle may ameliorate the precipitation-associated decrease in test day milk per milking cow.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.