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How our approaches to assessing benefits and harms can be improved

Published online by Cambridge University Press:  01 January 2023

ES Sena  and
GL Currie
ES Sena
Affiliation:
Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK Contact for correspondence and requests for reprints: emily.sena@ed.ac.uk
GL Currie
Affiliation:
Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
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Abstract

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Harm-benefit analysis (HBA) underpins the ethical framework of the regulation of animal experiments. This process involves a qualitative, and generally subjective, assessment of the potential benefits weighed against likely harms to be caused to animals. However, there is scope to prospectively quantify this process. A systematic and empirical assessment of historical data can give insights into why benefits are not realised and the magnitude of harm that animals experience. There is substantial scholarly evidence that risks to the 3Vs, the three core aspects of experimental validity in animal experiments (internal, external and construct validity) and low statistical power are limiting the reliability and reproducibility of research. Assessment of the 3Rs (reduction, refinement and replacement) is embedded in HBA and specifically seeks to minimise harm to the animals. However, no formal structure is in place to assess the likelihood of benefit, and we champion the 3Vs as a scale with which this may be achieved. Ethical approval procedures that consider the 3Vs and 3Rs using meta-research may be an approach to facilitate HBA. In ethical considerations related to animal research, there are value judgements that are integral to HBA, which cannot be measured directly. However, a quantitative and systematic approach is likely to be of added value. The perspective and examples described in this paper relate to laboratory animal research, but the approaches may lend themselves to different settings involving animals to ensure that decision-making and changes introduced, for example, to improve animal welfare, are evidence-based.

Keywords

animal welfarebenefitexperimental validityharmlaboratory researchmeta-research
Type
Articles
Information
Animal Welfare , Volume 28 , Issue 1 , February 2019 , pp. 107 - 115
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of The Universities Federation for Animal Welfare

References

Antonic, A, Sena, ES, Lees, JS, Wills, TE, Skeers, P, Batchelor, PE, Macleod, MR and Howells, DW 2013 Stem cell transplantation in traumatic spinal cord injury: a systematic review and meta-analysis of animal studies. PLoS Biology 11: e1001738. https://doi.org/10.1371/journal.pbio.1001738CrossRefGoogle ScholarPubMed
Bateson, P 1986 When to experiment on animals. New Scientist 109: 30–32Google ScholarPubMed
Bateson, P 2005 Ethics and behavioral biology. Advances in the Study of Behaviour pp 211–233. http://www.psych.utoronto.ca/users/psy3001/files/Bateson%202005.pdf 10.1016/S0065-3454(05)35005-4CrossRefGoogle Scholar
Baumans, V 2005 Environmental enrichment for laboratory rodents and rabbits: requirements of rodents, rabbits, and research. ILAR Journal 46: 162–170. https://doi.org/10.1093/ilar.46.2.162CrossRefGoogle ScholarPubMed
Beynen, A, Gärtner, K and van Zutphen, L 2003 Standardisation of animal experimentation. In: Zutphen, L, Baumans, V and Beynen, A (eds) Principles of Laboratory Animal Science pp 103–110. Elsevier: Amsterdam, The NetherlandsGoogle Scholar
Chambers, CD, Feredoes, E, Muthukumaraswamy, S and Etchells, P 2014 Instead of ‘playing the game’ it is time to change the rules: Registered Reports at AIMS Neuroscience and beyond. AIMS Neuroscience 1: 4–17. https://doi.org/10.3934/Neuroscience.2014.1.4CrossRefGoogle Scholar
Crabbe, JC, Wahlsten, D and Dudek, BC 1999 Genetics of mouse behavior: interactions with laboratory environment. Science 284: 1670–1672. https://doi.org/10.1126/sci-ence.284.5420.1670CrossRefGoogle ScholarPubMed
Crossley, NA, Sena, E, Goehler, J, Horn, J, van der Worp, B, Bath, PMW, Macleod, M and Dirnagl, U 2008 Empirical evi-dence of bias in the design of experimental stroke studies: A metaepidemiologic approach. Stroke 39: 929–934. https://doi.org/10.1161/STROKEAHA.107.498725CrossRefGoogle Scholar
Currie, GL, Angel-Scott, H, Colvin, L, Cramond, F, Hair, K, Khandoker, L, Liao, J, Macleod, MR, McCann, SK, Morland, R, Sherratt, N, Stewart, R, Tanriver-Ayder, E, Thomas, J, Wang, Q, Wodarski, R, Xiong, R, Rice, ASC and Sena, ES 2018 Animal models of chemotherapy-induced peripheral neu-ropathy: a machine-assisted systematic review and meta-analysis A comprehensive summary of the field to inform robust experi-mental design. bioRxiv 293480. https://doi.org/10.1101/293480CrossRefGoogle Scholar
Davies, GF 2018 Harm-benefit analysis: opportunities for enhancing ethical review in animal research. Laboratory Animals (NY) 47: 57–58. https://doi.org/10.1038/s41684-018-0002-2CrossRefGoogle ScholarPubMed
Festing, MFW and Altman, DG 2002 Guidelines for the design and statistical analysis of experiments using laboratory animals. ILAR Journal/National Research Council, Institute of Laboratory Animal Resources 43: 244–258. https://doi.org/10.1093/ilar.43.4.244CrossRefGoogle Scholar
Festing, MFW and Altman, DG 2005 Guidelines for the design and statistical analysis of experiments using laboratory aminals. ILAR Journal/National Research Council, Institute of Laboratory Animal Resources 43: 244–258. https://doi.org/10.1093/ilar.43.4.244CrossRefGoogle Scholar
Hirst, T, Vesterinen, H, Sena, E, Egan, K, Macleod, M and Whittle, I 2013 Systematic review and meta-analysis of temo-zolomide in animal models of glioma: was clinical efficacy predict-ed? British Journal of Cancer 108: 64–71. https://doi.org/10.1038/bjc.2012.504CrossRefGoogle Scholar
Hooijmans, CR, de Vries, RBM, Ritskes-Hoitinga, M, Rovers, MM, Leeflang, MM, IntHout, J, Wever, KE, Hooft, L, de Beer, H, Kuijpers, T, Macleod, MR, Sena, ES, ter Riet, G, Morgan, RL, Thayer, KA, Rooney, AA, Guyatt, GH, Schünemann, HJ, Langendam, MW and on behalf of the GWG 2018 Facilitating healthcare decisions by assessing the certainty in the evidence from preclinical animal studies. PLoS One 13: e018727110.1371/journal.pone.0187271CrossRefGoogle ScholarPubMed
Ioannidis, JPA 2005 Why most published research findings are false. PLoS Medicine 2: 696–701. https://doi.org/10.1371/journal.pmed.0020124CrossRefGoogle ScholarPubMed
Ioannidis, JPA, Fanelli, D, Dunne, DD and Goodman, SN 2015 Meta-research: Evaluation and improvement of research methods and practices. PLoS Biology 13: e1002264. https://doi.org/10.1371/journal.pbio.1002264CrossRefGoogle ScholarPubMed
Kafkafi, N, Golani, I, Jaljuli, I, Morgan, H, Sarig, T, Wurbel, H, Yaacoby, S and Benjamini, Y 2017 Addressing reproducibility in single-laboratory phenotyping experiments. Nature Methods 14:462–464. https://doi.org/10.1038/nmeth.4259CrossRefGoogle ScholarPubMed
Kimmelman, J, Mogil, JS and Dirnagl, U 2014 Distinguishing between exploratory and confirmatory preclinical research will improve translation. PLoS Biology 12(5): e1001863. https://doi.org/10.1371/journal.pbio.1001863CrossRefGoogle ScholarPubMed
Leaman, J 2014 Attitudes to animal research in 2014. A report by Ipsos MORI for the Department for Business, Innovation & Skills. https://www.ipsos.com/sites/default/files/migrations/en-uk/files/Assets/Docs/Polls/sri_BISanimalresearch_TRENDreport.pdfGoogle Scholar
Macleod, MR, Lawson, MA, Kyriakopoulou, A, Serghiou, S, de, WA, Sherratt, N, Hirst, T, Hemblade, R, Bahor, Z, Nunes-Fonseca, C, Potluru, A, Thomson, A, Baginskaite, J, Egan, K, Vesterinen, H, Currie, GL, Churilov, L, Howells, DW and Sena, ES 2015 Risk of bias in reports of in vivo research: A focus for improvement. PLoS Biology 13: e100227310.1371/journal.pbio.1002273CrossRefGoogle ScholarPubMed
Macleod, MR, van der Worp, HB, Sena, ES, Howells, DW, Dirnagl, U and Donnan, GA 2008 Evidence for the efficacy of NXY-059 in experimental focal cerebral ischaemia is confounded by study quality. Stroke 39: 2824–2829. https://doi.org/10.1161/STROKEAHA.108.515957CrossRefGoogle ScholarPubMed
Macrae, IM 2011 Preclinical stroke research: advantages and dis-advantages of the most common rodent models of focal ischaemia. British Journal of Pharmacology 164: 1062–1078. https://doi.org/10.1111/j.1476-5381.2011.01398.xCrossRefGoogle Scholar
McCann, SK, Cramond, F, Macleod, MR and Sena, ES 2016 Systematic review and meta-analysis of the efficacy of interleukin-1 receptor antagonist in animal models of stroke: an update. Translational Stroke Research 7: 395–406. https://doi.org/10.1007/s12975-016-0489-zCrossRefGoogle ScholarPubMed
Minnerup, J, Zentsch, V, Schmidt, A, Fisher, M and Schabitz, WR 2016 Methodological quality of experimental stroke studies published in the stroke journal: time trends and effect of the basic science checklist. Stroke 47: 267–272. https://doi.org/10.1161/STROKEAHA.115.011695CrossRefGoogle ScholarPubMed
Mogil, JS and Macleod, MR 2017 No publication without con-firmation. Nature 542: 409–411. https://doi.org/10.1038/542409aCrossRefGoogle Scholar
Moorthy, VS, Karam, G, Vannice, KS and Kieny, MP 2015 Rationale for WHO's new position calling for prompt reporting and public disclosure of interventional clinical trial results. PLoS Medicine 12: e1001819. https://doi.org/10.1371/journal.pmed.1001819CrossRefGoogle ScholarPubMed
Nosek, BA and Errington, TM 2017 Making sense of replications. eLife 6: e23383. https://doi.org/10.7554/eLife.23383CrossRefGoogle ScholarPubMed
O'collins, VE, Macleod, MR, Donnan, GA, Horky, LL, van der Worp, BH and Howells, DW 2006 1,026 experimental treatments in acute stroke. Annals of Neurology 59: 467–477. https://doi.org/10.1002/ana.20741CrossRefGoogle Scholar
Paylor, R 2009 Questioning standardization in science. Nature Methods 6: 253–254. https://doi.org/10.1038/nmeth0409-253CrossRefGoogle ScholarPubMed
Percie du Sert, N and Robinson, V 2018 The NC3Rs gateway: Accelerating scientific discoveries with new 3Rs models and tech-nologies. F1000Research 7: 591. Phttps://doi.org/10.12688/f1000research.14964.1CrossRefGoogle Scholar
Pound, P and Nicol, CJ 2018 Retrospective harm benefit analysis of pre-clinical animal research for six treatment interventions. PLoS One 13: e0193758. https://doi.org/10.1371/journal.pone.0193758CrossRefGoogle ScholarPubMed
Richter, SH, Garner, JP, Auer, C, Kunert, J and Wuerbel, H 2010 Systematic variation improves reproducibility of animal experiments. Nature Methods 7: 167–16810.1038/nmeth0310-167CrossRefGoogle ScholarPubMed
Richter, SH, Garner, JP and Wuerbel, H 2009 Environmental standardization: cure or cause of poor reproducibility in animal experiments? Nature Methods 6: 257–26110.1038/nmeth.1312CrossRefGoogle ScholarPubMed
Richter, SH, Garner, JP, Zipser, B, Lewejohann, L, Sachser, N, Touma, C, Schindler, B, Chourbaji, S, Brandwein, C, Gass, P, van, SN, van der Harst, J, Spruijt, B, Voikar, V, Wolfer, DP and Wurbel, H 2011 Effect of population heterog-enization on the reproducibility of mouse behavior: a multi-labo-ratory study. PLoS One 6: e1646110.1371/journal.pone.0016461CrossRefGoogle ScholarPubMed
Rooke, ED, Vesterinen, HM, Sena, ES, Egan, KJ and Macleod, MR 2011 Dopamine agonists in animal models of Parkinson's disease: A systematic review and meta-analysis. Parkinsonism & Related Disorders 17: 313–320. https://doi.org/10.1016/j.parkreldis.2011.02.010CrossRefGoogle ScholarPubMed
Russell, WMS and Burch, RL 1959 The Principles of Humane Experimental Technique. Methuen: London, UKGoogle Scholar
Sena, E, van der Worp, HB, Howells, D and Macleod, M 2007 How can we improve the pre-clinical development of drugs for stroke? Trends in Neurosciences 30: 433–439. https://doi.org/10.1016/j.tins.2007.06.009CrossRefGoogle ScholarPubMed
Sena, ES, van der Worp, HB, Bath, PMW, Howells, DW and Macleod, MR 2010 Publication bias in reports of animal stroke studies leads to major overstatement of efficacy. PLoS Biology 8: e1000344. https://doi.org/10.1371/journal.pbio.1000344CrossRefGoogle ScholarPubMed
Tsilidis, KK, Panagiotou, OA, Sena, ES, Aretouli, E, Evangelou, E, Howells, DW, Salman, RA-S, Macleod, MR and Ioannidis, JP 2013 Evaluation of excess significance bias in animal studies of neurological diseases. PLoS Biology 11(7): e1001609. https://doi.org/10.1371/journal.pbio.1001609CrossRefGoogle ScholarPubMed
van der Worp, HB, Howells, DW, Sena, ES, Porritt, MJ, Rewell, S, O'collins, V and Macleod, MR 2010 Can animal models of disease reliably inform human studies? PLoS Medicine 7: e1000245. https://doi.org/10.1371/journal.pmed.1000245CrossRefGoogle ScholarPubMed
van Luijk, J, Cuijpers, Y, van der Vaart, L, Leenaars, M and Ritskes-Hoitinga, M 2011 Assessing the search for information on Three Rs methods, and their subsequent implementation: a national survey among scientists in the Netherlands. Alternatives to Lab Animals 39: 429–44710.1177/026119291103900505CrossRefGoogle ScholarPubMed
Vesterinen, HM, Sena, ES, French-Constant, C, Williams, A, Chandran, S and Macleod, MR 2010 Improving the translational hit of experimental treatments in multiple sclerosis. Multiple Sclerosis 16: 1044–1055. https://doi.org/10.1177/1352458510379612CrossRefGoogle ScholarPubMed
Voelkl, B, Vogt, L, Sena, ES and Wuerbel, H 2018 Reproducibility of preclinical animal research improves with het-erogeneity of study samples. PLoS Biology 16: e2003693. https://doi.org/10.1371/journal.pbio.2003693CrossRefGoogle Scholar
Voelkl, B and Wurbel, H 2016 Reproducibility crisis: Are we Ignoring reaction norms? Trends Pharmacological Sciences 37: 509–510. https://doi.org/10.1016/j.tips.2016.05.003CrossRefGoogle ScholarPubMed
Vogt, L, Reichlin, TS, Nathues, C and Wurbel, H 2016 Authorization of animal experiments is based on confidence rather than evidence of scientific rigor. PLoS Biology 14: e2000598. https://doi.org/10.1371/journal.pbio.2000598CrossRefGoogle ScholarPubMed
Wieschowski, S, Chin, WWL, Federico, C, Sievers, S, Kimmelman, J and Strech, D 2018 Preclinical efficacy studies in investigator brochures: Do they enable risk-benefit assessment? PLoS Biology 16: e2004879. https://doi.org/10.1371/journal.pbio.2004879CrossRefGoogle ScholarPubMed
Wieschowski, S, Silva, DS and Strech, D 2016 Animal study registries: Results from a stakeholder analysis on potential strengths, weaknesses, facilitators, and barriers. PLoS Biology 14: e2000391. https://doi.org/10.1371/journal.pbio.2000391CrossRefGoogle ScholarPubMed
Willner, P and Mitchell, PJ 2002 The validity of animal models of predisposition to depression. Behavioural Pharmacology 13: 169–188. https://doi.org/10.1097/00008877-200205000-00001CrossRefGoogle ScholarPubMed
Wodarski, R, Delaney, A, Ultenius, C, Morland, R, Andrews, N, Baastrup, C, Bryden, LA, Caspani, O, Christoph, T, Gardiner, NJ, Huang, W, Kennedy, JD, Koyama, S, Li, D, Ligocki, M, Lindsten, A, Machin, I, Pekcec, A, Robens, A, Rotariu, SM, Vob, S, Segerdahl, M, Stenfors, C, Svensson, CI, Treede, RD, Uto, K, Yamamoto, K, Rutten, K and Rice, AS 2016 Cross-centre replication of suppressed burrowing behaviour as an ethologically relevant pain outcome measure in the rat: a prospective multicentre study. Pain 157: 2350–2365. https://doi.org/10.1097/j.pain.0000000000000657CrossRefGoogle Scholar
Wuerbel, H 2000 Behaviour and the standardization fallacy. Nature Genetics 26: 263. https://doi.org/10.1038/81541CrossRefGoogle Scholar
Wuerbel, H 2017 More than 3Rs: the importance of scientific validity for harm-benefit analysis of animal research. Laboratory Animals (NY) 46: 164–166. https://doi.org/10.1038/laban.1220CrossRefGoogle Scholar