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Meta-analysis of animal studies: a solution to animal waste

Animal research has always attracted a lot of attention because it involves the welfare of animals being compromised. Given this pressure, you would expect that animal studies are performed according to the highest scientific standards; however, there are big methodological problems. Many studies don’t use sound practices like randomization and blinding, which are needed to get unbiased results. Almost everything that gets published is claimed to be significant. Unpublished studies may lead to unnecessary replication. All this results in a waste of animals, time, money, and medical resources that could have been used for better scientific purposes. Moreover, patients can become unnecessarily exposed to non-effective treatments. All this reduces trust in animal study results.

Meta-analysis of animal studies may be part of the solution. Why are meta-analyses of animal studies important? In short: meta-analyses promote an efficient use of information. Many animals already have been sacrificed, so why not use this information? You can only spend your time and money once.

In a meta-analysis, multiple small animal studies are combined, which increases the power to answer a research question—for example, questions related to effects in subgroups. New conclusions can then be drawn without using new experimental animals, or if a new study is needed, meta-analysis may provide a solid rationale for its design and sample size. Note that while meta-analyses of clinical trials emphasize the summary effect, the focus for animal studies is often more on exploring the heterogeneity in the results and on the relation between this heterogeneity and study characteristics.

Furthermore, systematic reviews and meta-analyses of animal studies highlight shortcomings, which should lead to improvements. Researchers can improve the conduct of animal experiments with a better understanding of methodological quality and variations in design (such as species, gender, timing of treatment, etc.). Researchers can also apply lessons in efficiency from clinical meta-analysis, using software and steps designed for clinical meta-analyses for animal studies. Patient safety may increase, because errors in the translation of results from animal studies to clinical practice will be reduced. For example, in order to investigate why promising animal gene therapy research for cerebral glioma failed to translate into clinical efficacy, a meta-analysis in animal models was used. Indeed, it identified areas for improvement in conduct and reporting of the studies.

It is important that each scientist who conducts a meta-analysis of animal studies realizes that the quality of a meta-analysis is dependent on the quality of the primary studies. If the purpose of the meta-analysis is to inform healthcare policy or practice, the original research needs to be both applicable and of sufficient quality. Furthermore, it is important that only sensible comparisons are made in order to reduce the risk of false positive findings and diminish heterogeneity. It is therefore important to always conduct meta-analysis in collaboration with an expert from the field.

Meta-analyses of animal experiments may result in new and very valuable information from already-published experiments—and a better future for animal studies as a whole.

Image Credit: “Your life or My PhD?” by Mycroyance. CC BY NC 2.0 via Flickr.

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