Article

A call for transparent reporting to optimize the predictive value of preclinical research

National Institute of Neurological Disorders and Stroke, NIH, Bethesda, Maryland 20892, USA.
Nature (Impact Factor: 42.35). 10/2012; 490(7419):187-91. DOI: 10.1038/nature11556
Source: PubMed

ABSTRACT The US National Institute of Neurological Disorders and Stroke convened major stakeholders in June 2012 to discuss how to improve the methodological reporting of animal studies in grant applications and publications. The main workshop recommendation is that at a minimum studies should report on sample-size estimation, whether and how animals were randomized, whether investigators were blind to the treatment, and the handling of data. We recognize that achieving a meaningful improvement in the quality of reporting will require a concerted effort by investigators, reviewers, funding agencies and journal editors. Requiring better reporting of animal studies will raise awareness of the importance of rigorous study design to accelerate scientific progress.

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    • "Similar suggestions have been made for biological studies (Kozlov and Hurlbert, 2006; Verbitsky, 2013) and research in sports medicine and sports science (Hayen, 2006). It was recently noted that when a biological variation in response to some intervention was the variable of interest in the analysis of samples, considering the natural grouping of objects was essential (Landis et al., 2012). Therefore, the current study has three main goals: (i) to determine gender differences in start reaction times for four different 50 m stroke final events at six Swimming World Championships, (ii) to assess the effects of ignoring natural groupings at Swimming World Championships, and (iii) to evaluate the effects of the large sample size on statistical inferences when gender differences are examined with respect to start reaction times among elite swimmers at Swimming World Championships. "
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    • "The non mammalian studies had " probably high " risk of bias for the sequence generation, allocation concealment, and blinding domains. Because these components have been shown empirically to influence study outcomes in experimental animal studies (Bebarta et al. 2003; Landis et al. 2012; Macleod et al. 2004), our group consensus was to downgrade each non human body of evidence by one quality level (–1) for risk of bias across studies. "
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