How the type of risk reduction influences required sample sizes in randomised clinical trials
Open accessAbstract
To increase change between groups, randomised clinical trials (RCT) often include patients with high risk for a particular outcome, by inclusion criteria that select predictors for that outcome. This increases the statistical power, and fewer patients are required for that RCT. The way in which patient selection influences the power, and thus sample size required, depends on how an intervention reduces the individual risk: by an absolute or relative risk reduction model.
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To test clinical endpoints of severe infections, hospitalizations, and death, participants selected for a clinical trial should have a higher risk of these conditions than healthy people.
“Additionally, healthy people were enrolled in the clinical trials—but in order to test the clinical endpoints of severe infections, hospitalizations, and death, participants selected for a clinical trial should have a higher risk of these conditions than healthy people. Randomized clinical trials “often include patients with a high prior risk for the outcome of interest” [35].”
From Relative risk reduction: Misinformative measure in clinical trials and COVID-19 vaccine efficacy (2022) · cites this paper as [35]
The Abstract says RCTs often select patients at high prior risk for the outcome of interest, matching the quoted sentence. The Further Comments recommend high-risk selection as a rule of thumb for statistical power, but also discuss reasons to include other risk groups. The paper does not address severe infections, hospitalizations, death, or a comparison with healthy participants, so it does not establish that high-risk selection is required for those endpoints. (LLM, conf=0.86)
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Relative risk reduction: Misinformative measure in clinical trials and COVID-19 vaccine efficacy
Brown, R. B. (2022) · Dialogues in Health · doi:10.1016/j.dialog.2022.100074 · Cited by 11 · see citing works
“Randomized clinical trials “ often include patients with a high prior risk for the outcome of interest ” [35].”
- Authors
- Bruynesteyn, K., Wanders, A., Landewé, R., & van der Heijde, D.
- Affiliations
- Maastricht University Medical Centre (NL)
- Maastricht University (NL)
- ORCID
- Landewé, R
- Venue
- Annals of the Rheumatic Diseases
- Publisher
- Elsevier BV
- Published
- 2004-11
- Volume
- 63
- Issue
- 11
- Pages
- 1368-1371
- ISSN
- 0003-4967 (ISSN-L)
- PMC
- PMC1754827
- OpenAlex
- W2144197004
- Cited by
- 5
- References
- 0
- Citations by year
- 2025: 1 · 2022: 1 · 2016: 1 · 2012: 1
- FWCI
- 0.32
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Annals of the Rheumatic Diseases (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- sample size, statistical power, randomized controlled trials, risk mitigation, absolute risk reduction, relative risk reduction, patient selection, inclusion criteria, prognostic factors
- MeSH terms
- Humans, Rheumatology, Randomized Controlled Trials as Topic, Sample Size, Patient Selection
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