SyRF: the CAMARADES/NC3Rs in vivo systematic review and meta-analysis facility

Aims

This infrastructure award will maximise the 3Rs potential of undertaking systematic reviews and meta-analyses of animal research.

Background

Systematic reviews and meta-analyses are common practice in clinical research. They remain relatively under-utilised in animal research although recent reviews have illustrated their potential 3Rs benefits for example, supporting a reduction in animal numbers, determining whether high severity tests or multiple tests are necessary, and avoiding the use of uninformative models.

Research details and methods

The award will support the development of online resources and hands-on support facilitating the wider use of systematic reviews and meta-analyses by researchers.

Visit the SyRF website or our experimental design hub to learn more.

Systematic review and meta-analysis can provide empirical evidence of the impact of internal and external validity of in vivo studies across research domains. We spend substantial time supporting those who wish to conduct such reviews in their own fields through methodological advice and support, a data repository, and access to our database.

This database can now be used in the analysis of diverse data, from animal models of stroke to receptor binding assays. It includes data from over 3,000 publications involving over 80,000 animals. Currently, we curate data on MS Access, accessed by external users via a secure remote desktop connection; migration to an SQL server based database will improve system performance, scalability and accessibility. Providing web based access backed up by the support of a research will substantially improve our effectiveness in supporting such activity. We will also provide user manuals, online training materials and telephone advice.

Our support will include systematic reviews and meta-analyses of preclinical studies, with calculation of summary effect sizes and determination in that model system of the impact of study design features and risk of bias items. For a given disease model, we will identify the outcome measure with the smallest variance. This will help reduce the number of animals used in future studies. We will provide information for power calculations, so that the number of animals sacrificed in studies are neither too small to detect reliably the effect being sought or unnecessarily large. We will determine whether high severity, multiple and lengthy experiments provide more information than low severity, single, short experiments. This will inform ethical considerations about the choice of measures to be used, supporting a reduction in the suffering of the animals. We will undertake secondary analyses investigating issues such as publication bias, and improvements in the quality of study reports over time. 

Jue TR et al. (2018). A systematic review and meta-analysis of topoisomerase inhibition in pre-clinical glioma models. Oncotarget 9(13):11387-11401. doi: 10.18632/oncotarget.24334

Akl EA et al. (2017). Living systematic reviews: 4. Living guideline recommendations. Journal of Clinical Epidemiology 91:47-53. doi: 10.1016/j.jclinepi.2017.08.009

Archer DP et al. (2017). Anesthetic Neuroprotection in Experimental Stroke in Rodents: A Systematic Review and Meta-analysis. Anesthesiology 126(4):653-65. doi: 10.1097/ALN.0000000000001534

Elliott JH et al. (2017). Living systematic review: 1. Introduction-the why, what, when, and how. Journal of Clinical Epidemiology 91:23-30. doi: 10.1016/j.jclinepi.2017.08.010

Flynn LMC et al. (2017). Alpha Calcitonin Gene-Related Peptide Increases Cerebral Vessel Diameter in Animal Models of Subarachnoid Hemorrhage: A Systematic Review and Meta-analysis. Frontiers in Neurology 8:357. doi: 10.3389/fneur.2017.00357

Sadigh-Eteghad S et al. (2017). D-galactose-induced brain ageing model: A systematic review and meta-analysis on cognitive outcomes and oxidative stress indices. PloS One 12(8):e0184122. doi: 10.1371/journal.pone.0184122

Simmonds M et al. (2017). Living systematic reviews: 3. Statistical methods for updating meta-analyses. Journal of Clinical Epidemiology 91:38-46. doi: 10.1016/j.jclinepi.2017.08.008

Thomas J et al. (2017). Living systematic reviews: 2. Combining human and machine effort. Journal of Clinical Epidemiology 91:31-37. doi: 10.1016/j.jclinepi.2017.08.011

Lalu MM et al. (2016). Evaluating mesenchymal stem cell therapy for sepsis with preclinical meta-analyses prior to initiating a first-in-human trial. eLife 5 doi: 10.7554/eLife.17850

van Hout GP et al. (2016). Translational failure of anti-inflammatory compounds for myocardial infarction: a meta-analysis of large animal models. Cardiovascular Research 109(2):240-8. doi: 10.1093/cvr/cvv239 

Zwetsloot PP et al. (2016). Cardiac Stem Cell Treatment in Myocardial Infarction: A Systematic Review and Meta-Analysis of Preclinical Studies. Circulation Research 118(8):1223-32. doi: 10.1161/CIRCRESAHA.115.307676 

Currie GL, Macleod MR (2015). Increasing value and reducing waste in animal models of rheumatological disease. International Journal of Rheumatic Diseases 18(5):485-7. doi: 10.1111/1756-185X.12703 

Jansen Of Lorkeers SJ et al. (2015). Similar effect of autologous and allogeneic cell therapy for ischemic heart disease: systematic review and meta-analysis of large animal studies. Circulation Research 116(1):80-6. doi: 10.1161/CIRCRESAHA.116.304872 

Laban KG et al. (2015). Effect of endothelin receptor antagonists on clinically relevant outcomes after experimental subarachnoid hemorrhage: a systematic review and meta-analysis. Journal of Cerebral Blood Flow and Metabolism 35(7):1085-9. doi: 10.1038/jcbfm.2015.89

Macleod M (2015). Prof Benchie and Dr Athena-A modern tragedy. Evidence-based Preclinical Medicine 2(1):16-19. doi: 10.1002/ebm2.8 

Macleod MR et al. (2015). Risk of Bias in Reports of In Vivo Research: A Focus for Improvement. PLOS Biology 13(10):e1002273. doi: 10.1371/journal.pbio.1002273 

Milidonis X et al. (2015). Magnetic resonance imaging in experimental stroke and comparison with histology: systematic review and meta-analysis. Stroke 46(3):843-51. doi: 10.1161/STROKEAHA.114.007560 

Vesterinen HM et al. (2015). Drug repurposing: a systematic approach to evaluate candidate oral neuroprotective interventions for secondary progressive multiple sclerosis. PLOS ONE 10(4):e0117705. doi: 10.1371/journal.pone.0117705 

Egan KJ et al. (2014). Exercise reduces infarct volume and facilitates neurobehavioral recovery: results from a systematic review and meta-analysis of exercise in experimental models of focal ischemia. Neurorehabilitation and Neural Repair 28(8):800-12. doi: 10.1177/1545968314521694 

Hirst TC et al. (2014). A systematic review and meta-analysis of gene therapy in animal models of cerebral glioma: why did promise not translate to human therapy? Evidence-based Preclinical Medicine 1(1):21-33. doi: 10.1002/ebm2.6 

Howells DW et al. (2014). Bringing rigour to translational medicine. Nature Reviews Neurology 10(1):37-43. doi: 10.1038/nrneurol.2013.232 

Ioannidis JP et al. (2014). Increasing value and reducing waste in research design, conduct, and analysis. Lancet 383(9912):166-75. doi: 10.1016/S0140-6736(13)62227-8 

Lalu MM et al. (2014). Efficacy and safety of mesenchymal stromal cells in preclinical models of acute lung injury: a systematic review protocol. Systematic Reviews 3:48. doi: 10.1186/2046-4053-3-48 

Macleod MR (2014). Preclinical research: Design animal studies better. Nature 510(7503):35. doi: 10.1038/510035a 

McCann SK et al. (2014). Efficacy of antidepressants in animal models of ischemic stroke: a systematic review and meta-analysis. Stroke 45(10):3055-63. doi: 10.1161/STROKEAHA.114.006304 

Pedder H et al. (2014). Systematic review and meta-analysis of interventions tested in animal models of lacunar stroke. Stroke 45(2):563-70. doi: 10.1161/STROKEAHA.113.003128 

Sena ES et al. (2014). Systematic reviews and meta-analysis of preclinical studies: why perform them and how to appraise them critically. Journal of Cerebral Blood Flow and Metabolism 34(5):737-42. doi: 10.1038/jcbfm.2014.28 

Vesterinen HM et al. (2014). Meta-analysis of data from animal studies: a practical guide. Journal of Neuroscience Methods 221:92-102. doi: 10.1016/j.jneumeth.2013.09.010 

Watzlawick R et al. (2014). Effect and reporting bias of RhoA/ROCK-blockade intervention on locomotor recovery after spinal cord injury: a systematic review and meta-analysis. JAMA Neurology 71(1):91-9. doi: 10.1001/jamaneurol.2013.4684

Wu S et al. (2014). Edaravone improves functional and structural outcomes in animal models of focal cerebral ischemia: a systematic review. International Journal of Stroke 9(1):101-6. doi: 10.1111/ijs.12163

Batchelor PE et al. (2013). Meta-analysis of pre-clinical studies of early decompression in acute spinal cord injury: a battle of time and pressure. PLOS ONE 8(8):e72659. doi: 10.1371/journal.pone.0072659 

Batchelor PE et al. (2013). Systematic review and meta-analysis of therapeutic hypothermia in animal models of spinal cord injury. PLOS ONE 8(8):e71317. doi: 10.1371/journal.pone.0071317 

Back to top
Infrastructure grant

Status:

Closed

Principal investigator

Professor Malcolm Macleod

Institution

University of Edinburgh

Co-Investigator

Dr Emily Sena

Grant reference number

NC/L000970/1

Award date:

Oct 2013 - Sep 2018

Grant amount

£504,931