48 research outputs found
A systematic review and meta-analysis of salivary cortisol measurement in domestic canines
Salivary cortisol is widely used as an indicator of stress and welfare in canine research. However, much remains unclear about the basic features of this hormone marker in domestic dogs. This systematic review and meta-analysis aimed to determine a reference range for cortisol concentration in the saliva of dogs and examine how canine characteristics, environmental effects and experimental considerations relate to salivary cortisol concentrations. A systematic review of literature databases and conference proceedings from 1992 to 2012 identified 61 peer-reviewed studies using domestic dog salivary cortisol. Researchers were contacted via email, and 31 raw data sets representing a total of 5,153 samples from 1,205 dogs were shared. Meta-analysis provided a cortisol concentration range of 0 to 33.79 μg/dL (mean 0.45 μg/dL, SEM 0.13). Significant effects (P < 0.05) were found for sex and neuter status, age, regular living environment, time in environment before testing, testing environment, owner presence during testing, and collection media. Significant effects were not found for dog breed, body weight, dog type, coat color, assay type, exercise, eating, or use of salivary stimulant. Care should be taken when using cortisol studies for dogs at a group or population level as there is a large amount of intraindividual and interindividual variability and external variables could influence salivary cortisol concentration. This analysis highlights the importance of carefully controlling experimental design to compare samples within and between individual dogs, as well as establishing and using best practices for saliva collection. Caution should be exercised in comparing different studies, as the results could be the reflection of a plethora of factors
Review and update of leukemia risk potentially associated with occupational exposure to benzene.
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Use of Retrospective Data for Comparative Effectiveness Research Yields Mixed Outcomes and Should be Avoided.
Purpose/objective(s)In oncology, retrospective cohort studies are often used for comparative effectiveness research, studies that compare the efficacy of treatment A vs B. We examine the stability of these estimates using biostatistical methods for bias correction with varying sets of covariates. We hypothesize that retrospective comparative effectiveness research studies are sensitive to biostatistical analytic choices; by varying the methods, there will be significant instability and lack of consistency in conclusions.Materials/methodsWe evaluated three disease sites in oncology where the addition of local therapy over systemic therapy alone has been hypothesized to improve survival in the metastatic setting: lung, prostate, and female breast, using multivariable Cox regression analyses. Patient data were extracted from the National Cancer Database, 2004-2014. We employed various statistical techniques to adjust for selection bias and immortal time bias, including propensity score matching, left truncation adjustment, and landmark analysis. Further, we used combinations of covariates in regression models to generate hazard ratios (HRs) with 95% confidence intervals. We constructed plots of -log10(P-value) vs HR to quantify the variability of estimates.ResultsThere were 72,549 lung, 14,904 prostate, and 13,857 female breast cancer patients included. We ran > 300,000 regression models, where each model represents a publishable study. Without propensity score matching or immortal time bias adjustment, all multivariable models provided HRs that favored the addition of local therapy for all cancers, with HRs < 1, and all P-values < 0.001. Once propensity score matching was added to our analysis, higher HRs were observed, but most were still < 1. When landmark analysis and covariate combinations were used, we generated HRs that were < 1, equal to 1, and > 1, with 100-fold differences in -log10(P-values).ConclusionBy altering the biostatistical approach with varying combinations of covariates, we were able to generate contrary outcomes and statistical significance. Our results suggest that some retrospective observational studies may find a treatment helps, and another may find it does not, simply based on analytic choices. This paradox highlights the importance of randomized controlled trials, and may explain the discordance noted in prior studies comparing observational trials and randomized studies