Evidence map›Paper›PMID 29296016›Full record

ArticleLab animal2017

Systematic heterogenization for better reproducibility in animal experimentation.

S Helene Richter

Abstract read
PubMed Publisher
In one paragraph

Article in Lab animal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

S Helene RichterRG Behavioural Biology and Animal Welfare, Institute of Neuro and Behavioural Biology, University of Münster, Münster, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The scientific literature is full of articles discussing poor reproducibility of findings from animal experiments as well as failures to translate results from preclinical animal studies to clinical trials in humans. Critics even go so far as to talk about a "reproducibility crisis" in the life sciences, a novel headword that increasingly finds its way into numerous high-impact journals. Viewed from a cynical perspective, Fett's law of the lab "Never replicate a successful experiment" has thus taken on a completely new meaning. So far, poor reproducibility and translational failures in animal experimentation have mostly been attributed to biased animal data, methodological pitfalls, current publication ethics and animal welfare constraints. More recently, the concept of standardization has also been identified as a potential source of these problems. By reducing within-experiment variation, rigorous standardization regimes limit the inference to the specific experimental conditions. In this way, however, individual phenotypic plasticity is largely neglected, resulting in statistically significant but possibly irrelevant findings that are not reproducible under slightly different conditions. By contrast, systematic heterogenization has been proposed as a concept to improve representativeness of study populations, contributing to improved external validity and hence improved reproducibility. While some first heterogenization studies are indeed very promising, it is still not clear how this approach can be transferred into practice in a logistically feasible and effective way. Thus, further research is needed to explore different heterogenization strategies as well as alternative routes toward better reproducibility in animal experimentation.

Indexed as

Reproducibility of ResultsResearch DesignAnimal ExperimentationAnimalsBiasModels, Animal

Identifiers

PMID29296016

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.