Improving the translational hit of experimental treatments in multiple sclerosis
Abstract
Background In other neurological diseases, the failure to translate pre-clinical findings to effective clinical treatments has been partially attributed to bias introduced by shortcomings in the design of animal experiments. Objectives Here we evaluate published studies of interventions in animal models of multiple sclerosis for methodological design and quality and to identify candidate interventions with the best evidence of efficacy. Methods A systematic review of the literature describing experiments testing the effectiveness of interventions in animal models of multiple sclerosis was carried out. Data were extracted for reported study quality and design and for neurobehavioural outcome. Weighted mean difference meta-analysis was used to provide summary estimates of the efficacy for drugs where this was reported in five or more publications. Results The use of a drug in a pre-clinical multiple sclerosis model was reported in 1152 publications, of which 1117 were experimental autoimmune encephalomyelitis (EAE). For 36 interventions analysed in greater detail, neurobehavioural score was improved by 39.6% (95% CI 34.9-44.2%, p Conclusions EAE has proven to be a valuable model in elucidating pathogenesis as well as identifying candidate therapies for multiple sclerosis. However, there is an inconsistent application of measures to limit bias that could be addressed by adopting methodological best practice in study design. Our analysis provides an estimate of sample size requir…
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Compelling data from systematic reviews show that nonblinded outcome assessment leads to treatment effects being overestimated.
“There are, however, compelling data from systematic reviews showing that nonblinded outcome assessment leads to the treatment effects being overestimated, and the lack of bias-reducing measures such as randomisation and blinding can contribute to as much as 30%–45% inflation of effect sizes [67,68,85].”
From Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0 (2020) · cites this paper as [68]
Systematic reviews have shown that animal experiments that do not report randomisation or other bias-reducing measures such as blinding are more likely to report exaggerated effects that meet conventional measures of statistical significance.
“Systematic reviews have shown that animal experiments that do not report randomisation or other bias-reducing measures such as blinding are more likely to report exaggerated effects that meet conventional measures of statistical significance [67–69].”
From Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0 (2020) · cites this paper as [68]
Lack of bias-reducing measures such as randomisation and blinding can contribute to as much as 30%-45% inflation of effect sizes.
“There are, however, compelling data from systematic reviews showing that nonblinded outcome assessment leads to the treatment effects being overestimated, and the lack of bias-reducing measures such as randomisation and blinding can contribute to as much as 30%–45% inflation of effect sizes [67,68,85].”
From Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0 (2020) · cites this paper as [68]
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- Authors
- Vesterinen, H. M., Sena, E. S., ffrench-Constant, C., Williams, A., Chandran, S., & Macleod, M. R.
- Affiliations
- Western General Hospital (GB)
- Centre for Clinical Brain Sciences, Department of Clinical Neurosciences, University of Edinburgh, Western General Hospital, UK
- Corresponding author
- Macleod, Malcolm R
- Venue
- Multiple Sclerosis Journal
- Publisher
- SAGE Publications
- Published
- 2010-08-04
- Volume
- 16
- Issue
- 9
- Pages
- 1044-1055
- ISSN
- 1352-4585 (ISSN-L)
- 1477-0970
- OpenAlex
- W2105381170
- Cited by
- 182
- References
- 2
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 7 · 2023: 10 · 2022: 10 · 2021: 6 · 2020: 12 · 2019: 15 · 2018: 7 · 2017: 7 · 2016: 18 · 2015: 10 · 2014: 27 · 2013: 18 · 2012: 7
- FWCI
- 8.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Multiple Sclerosis Journal (publishedVersion)
- PubMed (publishedVersion)
- UEA Digital Repository (University of East Anglia) (submittedVersion)
- Funders
- Wellcome Trust
- University of Edinburgh
- Topics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- multiple sclerosis, experimental autoimmune encephalomyelitis, animal models of disease, translational research, study design bias, randomization, blinding, neurobehavioral outcomes, sample size determination, drug efficacy
- MeSH terms
- Animals, Behavior, Animal, Disease Models, Animal, Encephalomyelitis, Autoimmune, Experimental, Humans, Immunologic Factors, Multiple Sclerosis, Research Design, Time Factors, Reproducibility of Results, Bias, Chi-Square Distribution, Sample Size, Endpoint Determination, Translational Research, Biomedical
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