Journal article
Much ado about something: a response to “COVID-19: underpowered randomised trials, or no randomised trials?”
- Abstract:
- Non-pharmaceutical interventions (NPI) for infectious diseases such as COVID-19 are particularly challenging given the complexities of what is both practical and ethical to randomize. We are often faced with the difficult decision between having weak trials or not having a trial at all. In a recent article, Dr. Atle Fretheim argues that statistically underpowered studies are still valuable, particularly in conjunction with other similar studies in meta-analysis in the context of the DANMASK-19 trial, asking "Surely, some trial evidence must be better than no trial evidence?" However, informative trials are not always feasible, and feasible trials are not always informative. In some cases, even a well-conducted but weakly designed and/or underpowered trial such as DANMASK-19 may be uninformative or worse, both individually and in a body of literature. Meta-analysis, for example, can only resolve issues of statistical power if there is a reasonable expectation of compatible well-designed trials. Uninformative designs may also invite misinformation. Here, we make the case that-when considering informativeness, ethics, and opportunity costs in addition to statistical power-"nothing" is often the better choice.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 486.3KB, Terms of use)
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- Publisher copy:
- 10.1186/s13063-021-05755-y
- Publication website:
- https://oda.oslomet.no/oda-xmlui/bitstream/11250/3131916/1/LeBlanc_2024_Ind.pdf
Authors
- Publisher:
- BioMed Central
- Journal:
- Trials More from this journal
- Volume:
- 22
- Issue:
- 1
- Pages:
- 780-780
- Article number:
- 780
- Publication date:
- 2021-11-07
- DOI:
- EISSN:
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1745-6215
- ISSN:
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1745-6215
- Language:
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English
- Keywords:
- Pubs id:
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1207756
- Local pid:
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pubs:1207756
- Source identifiers:
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W3212540543
- Deposit date:
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2026-03-26
- ARK identifier:
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Terms of use
- Copyright date:
- 2021
- Licence:
- CC Attribution (CC BY)
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