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Systematic reviews of animal studies

A comprehensive guide on the significance of systematic reviews in animal studies for designing clinical trials, understanding evidence gaps, and limitations. Learn about search strategies, data extraction, and analysis methods. Discover how to identify biases and improve research practice.

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Systematic reviews of animal studies

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  1. Systematic reviews of animal studies Malcolm Macleod

  2. Why do systematic reviews of animal studies? • To summarise existing data • To help design clinical trials • To understand where evidence is lacking • To understand the limitations of animal models

  3. Basic requirements • Understanding the model – or knowing someone who does • Clear a priori hypotheses • A clear search strategy with inclusion and exclusion criteria • Information and data management

  4. The importance of hypotheses • Observational research • Susceptible to identification of statistically significant but biologically meaningless spurious associations • If there isn’t a question for which you wish to know the answer, why are you doing it?

  5. Examples • “Hypothermia improves outcome in animal models of stroke” • “The efficacy of hypothermia in animal models of stroke depends on the degree of cooling” • “Evidence for the efficacy of NXY-059 is confounded by poor study quality” • “The evidence for efficacy of stroke dugs in animals is confounded by publication bias”

  6. Search strategy • What are you looking for … • Controlled studies testing the effect of hypothermia in an animal model of focal cerebral ischaemia brought about by occlusion of a cerebral artery, where outcome was measured as infarct size or neurobehavioural score. • Exclusion criteria • hypothermia was accomplished with use of a pharmacological agent that may also have an intrinsic neuroprotective property; • cooling was used to counteract (spontaneous) hyperthermia after MCAO; • brain cooling lasted <10 min, for example to counteract heating in models of photochemically induced cerebral infarction; • data were presented in a way not suitable for use in a meta-analysis (e.g. no information on group size, mean or variance); or if • mortality was the only outcome measure.

  7. Example search strategy Studies of hypothermia in animal models of acute ischaemic stroke were identified from … • PubMed, EMBASE and BIOSIS up till December 31, 200> with the search strategy [[[<cerebral> OR <brain> OR <neuron> OR <neuronal> OR <nervous>] AND [<ischemia> OR <ischaemia>]] OR <stroke>] AND [<hypothermia> OR <temperature>] (limit: animals) • hand searching of abstracts of scientific meetings of the International Society of Cerebral Blood Flow and Metabolism, the International Stroke Conference [‘Joint (International) Conference on Stroke and Cerebral Circulation’ before 2000] and the European Stroke Conference during the same time period; • reference lists of identified publications; and • requests to authors of identified publications

  8. Source selection • Download search results to reference management system (eg RefMan) • 2 investigators independently select sources against inclusion/ exclusion criteria • May have to retrieve full text • Discrepancies resolved by negotiation or in discussion with third investigator

  9. Data extraction • Publication meta-data

  10. Data extraction • Publication meta-data • Outcome data

  11. Data cleaning

  12. Data analysis • Standardised mean difference analysis • Weighted mean difference analysis • Normalised mean difference analysis • Fixed Effects • Random Effects • Meta-regression

  13. SMD s.d. e.s. = difference/s.d. “sd units” difference e.s. = n1-n2 “real” units WMD 0 mm3 n1 n2 250 mm3 NMD e.s. = d1/100% “percent improvement in outcome” d1 0% unlesioned 100% lesioned

  14. Testing significance • Partitioning of heterogeneity: • Observed heterogeneity = within group heterogeneity + between group heterogeneity • Test against chi squared distribution with n-1 degrees of freedom • Observational, so set high statistical bar

  15. Data analysis

  16. Demonstration

  17. So, what can it do …? • Describe a literature ….

  18. Estimate efficacy … • Hypothermia • 101 papers • 277 experiments • 3353 animals

  19. Describe efficacy in subgroups…

  20. Show potential sources of bias … NXY 059 9 publications 29 experiments 408 animals Improved outcome by 44% (35-53%)

  21. Illustrate publication bias … 991 publications

  22. Provide evidence to change practice … • Animals • Sample size calculation • Inclusion and exclusion criteria • Randomization • Allocation concealment • Reporting of animals excluded from analysis • Blinded assessment of outcome • Reporting potential conflicts of interest and study funding

  23. Further resources • http://www.camarades.info • http://www.camarades.info/index_files/papers.htm • malcolm.macleod@ed.ac.uk • The CAMARADES podcast … • http://www.camarades.info/index_files/podcasts/podcast.xml

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