Recommendations for Planning Pilot Studies in Clinical and Translational Research
Open accessAbstract
Advances in clinical and translation science are facilitated by building on prior knowledge gained through experimentation and observation. In the context of drug development, preclinical studies are followed by a progression of phase I through phase IV clinical trials. At each step, the study design and statistical strategies are framed around research questions that are prerequisites for the next phase. In other types of biomedical research, pilot studies are used for gathering preliminary support for the next research step. However, the phrase “pilot study” is liberally applied to projects with little or no funding, characteristic of studies with poorly developed research proposals, and usually conducted with no detailed thought of the subsequent study. In this article, we present a rigorous definition of a pilot study, offer recommendations for the design, analysis and sample size justification of pilot studies in clinical and translational research, and emphasize the important role that well‐designed pilot studies play in the advancement of science and scientific careers. Clin Trans Sci 2011; Volume 4: 332–337
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Moore et al. showed that sample sizes of 30, 50 and 70 provide 48%, 78% and 84% power to reject an acceptance rate of 85% or lower if the true acceptance rate is 95% using a 1-sided α = 0.05 binomial test.
“they showed that sample sizes of 30, 50 and 70 provide 48%, 78% and 84% power to reject an acceptance rate of 85% or lower if the true acceptance rate is 95% using a 1-sided α = 0.05 binomial test.”
From Determining sample size for progression criteria for pragmatic pilot RCTs: the hypothesis test strikes back! (2021) · cites this paper as [24]
In “Power Calculations for Hypothesis Testing” (section III, “Justify the Choice of Sample Size”; page not provided), Moore et al. give the stated sample sizes, powers, and test, but say the calculation is for detecting an acceptance rate of 85% or lower—not rejecting that rate. The citing sentence reverses the stated target of the test. (LLM, conf=0.88)
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Experimental — accuracy not yet measuredAs recommended by Moore et al., the anticipated level of precision of statistical estimators for variables of interest at three different sample sizes (20, 40, and 60) was calculated using longitudinal data from a sample of YA cancer survivors obtained by the research team.
“As recommended by Moore et al. [72], the anticipated level of precision of statistical estimators for variables of interest at three different sample sizes (20, 40, and 60) was calculated using longitudinal data from a sample of YA cancer survivors obtained by the research team.”
From Improving symptom management for survivors of young adult cancer: rationale and study protocol for a pilot randomized controlled trial (2024) · cites this paper as [72]
One-sided binomial tests of α = 0.05 were used to calculate power at various sample sizes based on feasibility and acceptability rates found in our prior studies.
“One-sided binomial tests of α = 0.05 were used to calculate power at various sample sizes [72] based on feasibility and acceptability rates found in our prior studies [73].”
From Improving symptom management for survivors of young adult cancer: rationale and study protocol for a pilot randomized controlled trial (2024) · cites this paper as [72]
Recruitment was stopped at 13 participants per arm, consistent with guidance on conducting pilot and feasibility studies.
“Recruitment was stopped at 13 per arm, in keeping with guidance on conducting pilot and feasibility studies [24, 25] (e.g., CONSORT [31]).”
The study exceeded recommendations for N = 12 per arm as the optimal sample size in a pilot RCT and meets sample size recommendations to assess feasibility and acceptability.
“However, as Moore and colleagues [25] recommend, our study exceeded recommendations for N = 12/arm as the optimal sample size in a pilot RCT, and meets sample size recommendations to assess feasibility and acceptability of the intervention [24, 25].”
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References 29 · Cited by 661
Research works printed but not linked: 2
- [2]Polit D Hungler B Nursing Research Principles and Methods 1999 Lippincott Philadelphia, PA.
- [12]van Belle G Statistical rules of thumb 2002 John Wiley and Sons, Inc New York, NY
- Authors
- Moore, C. G., Carter, R. E., Nietert, P. J., & Stewart, P. W.
- Affiliations
- University of Pittsburgh (US)
- Mayo Clinic (US)
- Medical University of South Carolina (US)
- University of North Carolina at Chapel Hill (US)
- Venue
- Clinical and Translational Science
- Publisher
- Wiley
- Published
- 2011-10
- Volume
- 4
- Issue
- 5
- Pages
- 332-337
- ISSN
- 1752-8054 (ISSN-L)
- 1752-8062
- PMC
- PMC3203750
- OpenAlex
- W2152696551
- Cited by
- 661
- References
- 29
- Citations by year
- 2026: 51 · 2025: 70 · 2024: 75 · 2023: 68 · 2022: 87 · 2021: 75 · 2020: 72 · 2019: 52 · 2018: 34 · 2017: 26 · 2016: 17 · 2015: 12 · 2014: 6 · 2013: 9 · 2012: 3
- FWCI
- 5.31
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Clinical and Translational Science (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- National Institutes of Health (UL1TR000005, RR024150, RR024153, RR029882, RR025747)
- National Center for Research Resources (UL1RR029882, UL1RR024153, UL1RR025747, UL1RR024150)
- National Center for Advancing Translational Sciences
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Health Professions › Health Information Management › Methodologies in Health Research and Practice
- Keywords
- pilot study, research design, sample size justification, statistical analysis, clinical research, translational research, drug development, research planning, research funding
- MeSH terms
- Career Mobility, Humans, Pilot Projects, Research Design, Sample Size, Translational Research, Biomedical
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