ArticlePLoS biology2021
Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research.
Article in PLoS biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 6 of them syntheses that pooled it.
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Who cites it
34 citing papers in PubMed, 6 syntheses or guidelines pooled it, 70 citations in OpenAlex.
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- Contemporary in vivo rodent electroconvulsive therapy (ECT) models in translational depression research: a systematic review.Translational psychiatry · 2025Pooled it
- ClinicalFrontiers in microbiology · 2025Pooled it
- Recommendations for robust and reproducible preclinical research in personalised medicine.BMC medicine · 2023Guideline
- Animal pollination increases stability of crop yield across spatial scales.Ecology letters · 2022Pooled it
- Fifty Years Later, and We Still Don't Know About Badges of Status.Ecology and evolution · 2026Article
- Commonalities in gene expression and methylation changes across two rat models of acquired epilepsy.Scientific reports · 2026Article
- Review
- Reconfiguration of brain-wide neural activity after early life adversity.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Reconfiguration of brain-wide neural activity after early life adversity.bioRxiv : the preprint server for biology · 2025Article
- Continent-wide differentiation of fitness traits and patterns of climate adaptation among European populations ofEvolution letters · 2025Article
- A method for quantifying and automatic grading of musculoskeletal ultrasound superb microvascular imaging based on dynamic analysis of optical flow model.Scientific reports · 2025Article
- A Novel Method for the Generation of Realistic Lung Nodules Visualized Under X-Ray Imaging.Tomography (Ann Arbor, Mich.) · 2024Article
- Current evidence on the efficacy of mental health smartphone apps for symptoms of depression and anxiety. A meta-analysis of 176 randomized controlled trials.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2024Article
- Accelerating the open research agenda to solve global challenges.Ecology and evolution · 2024Article
- Protocol for the systematic review of age and sex in preclinical models of age-correlated diseases.F1000Research · 2024Article
- Article
- Muscarinic receptor agonists and positive allosteric modulators in animal models of psychosis: protocol for a systematic review and meta-analysis.F1000Research · 2024Article
- Finding the right power balance: Better study design and collaboration can reduce dependence on statistical power.PLoS biology · 2024Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The replicability of research results has been a cause of increasing concern to the scientific community. The long-held belief that experimental standardization begets replicability has also been recently challenged, with the observation that the reduction of variability within studies can lead to idiosyncratic, lab-specific results that cannot be replicated. An alternative approach is to, instead, deliberately introduce heterogeneity, known as "heterogenization" of experimental design. Here, we explore a novel perspective in the heterogenization program in a meta-analysis of variability in observed phenotypic outcomes in both control and experimental animal models of ischemic stroke. First, by quantifying interindividual variability across control groups, we illustrate that the amount of heterogeneity in disease state (infarct volume) differs according to methodological approach, for example, in disease induction methods and disease models. We argue that such methods may improve replicability by creating diverse and representative distribution of baseline disease state in the reference group, against which treatment efficacy is assessed. Second, we illustrate how meta-analysis can be used to simultaneously assess efficacy and stability (i.e., mean effect and among-individual variability). We identify treatments that have efficacy and are generalizable to the population level (i.e., low interindividual variability), as well as those where there is high interindividual variability in response; for these, latter treatments translation to a clinical setting may require nuance. We argue that by embracing rather than seeking to minimize variability in phenotypic outcomes, we can motivate the shift toward heterogenization and improve both the replicability and generalizability of preclinical research.
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Registered trials
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.