Author
Listed:
- Carlijn R Hooijmans
- Rob B M de Vries
- Merel Ritskes-Hoitinga
- Maroeska M Rovers
- Mariska M Leeflang
- Joanna IntHout
- Kimberley E Wever
- Lotty Hooft
- Hans de Beer
- Ton Kuijpers
- Malcolm R Macleod
- Emily S Sena
- Gerben ter Riet
- Rebecca L Morgan
- Kristina A Thayer
- Andrew A Rooney
- Gordon H Guyatt
- Holger J Schünemann
- Miranda W Langendam
- on behalf of the GRADE Working Group
Abstract
Laboratory animal studies are used in a wide range of human health related research areas, such as basic biomedical research, drug research, experimental surgery and environmental health. The results of these studies can be used to inform decisions regarding clinical research in humans, for example the decision to proceed to clinical trials. If the research question relates to potential harms with no expectation of benefit (e.g., toxicology), studies in experimental animals may provide the only relevant or controlled data and directly inform clinical management decisions.Systematic reviews and meta-analyses are important tools to provide robust and informative evidence summaries of these animal studies. Rating how certain we are about the evidence could provide important information about the translational probability of findings in experimental animal studies to clinical practice and probably improve it. Evidence summaries and certainty in the evidence ratings could also be used (1) to support selection of interventions with best therapeutic potential to be tested in clinical trials, (2) to justify a regulatory decision limiting human exposure (to drug or toxin), or to (3) support decisions on the utility of further animal experiments. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach is the most widely used framework to rate the certainty in the evidence and strength of health care recommendations. Here we present how the GRADE approach could be used to rate the certainty in the evidence of preclinical animal studies in the context of therapeutic interventions. We also discuss the methodological challenges that we identified, and for which further work is needed. Examples are defining the importance of consistency within and across animal species and using GRADE’s indirectness domain as a tool to predict translation from animal models to humans.
Suggested Citation
Carlijn R Hooijmans & Rob B M de Vries & Merel Ritskes-Hoitinga & Maroeska M Rovers & Mariska M Leeflang & Joanna IntHout & Kimberley E Wever & Lotty Hooft & Hans de Beer & Ton Kuijpers & Malcolm R Ma, 2018.
"Facilitating healthcare decisions by assessing the certainty in the evidence from preclinical animal studies,"
PLOS ONE, Public Library of Science, vol. 13(1), pages 1-18, January.
Handle:
RePEc:plo:pone00:0187271
DOI: 10.1371/journal.pone.0187271
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Citations
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Cited by:
- Gillian L Currie & Helena N Angel-Scott & Lesley Colvin & Fala Cramond & Kaitlyn Hair & Laila Khandoker & Jing Liao & Malcolm Macleod & Sarah K McCann & Rosie Morland & Nicki Sherratt & Robert Stewart, 2019.
"Animal models of chemotherapy-induced peripheral neuropathy: A machine-assisted systematic review and meta-analysis,"
PLOS Biology, Public Library of Science, vol. 17(5), pages 1-34, May.
- Olivia Hogue & Tucker Harvey & Dena Crozier & Claire Sonneborn & Abagail Postle & Hunter Block-Beach & Eashwar Somasundaram & Francis J May & Monica Snyder Braun & Felicia L Pasadyn & Khandi King & Ca, 2022.
"Statistical practice and transparent reporting in the neurosciences: Preclinical motor behavioral experiments,"
PLOS ONE, Public Library of Science, vol. 17(3), pages 1-17, March.
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