From a mouse: systematic analysis reveals limitations of experiments testing interventions in Alzheimer’s disease mouse models.

Systematic review and meta-analysis are powerful tools to assess the validity and robustness of data published in a certain research field. In this article, Egan et al. used a systematic review approach to analyze the prevalence and impact of quality factors known to influence the risk of bias (e.g. reporting of random allocation to group, blinded assessment of outcome, sample size calculation, compliance with animal welfare legislation and a statement declaring a possible conflict of interest) in the literature using the example of Alzheimer’s disease models. The authors found that only a few studies report fundamental aspects of study qualities (e.g. blinding, randomization) and that the risk of bias indeed impacts the observed efficacy. In summary, this article demonstrates the need to develop more precise standards and guidelines on how to decrease the risk of overstating efficacy from experiments conducted in animal models and how to build confidence in data obtained from preclinical animal studies. LINK

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