The statistical interpretation of pilot trials: should significance thresholds be reconsidered?

Lee, Ellen C; Whitehead, Amy L; Jacques, Richard M; Julious, Steven A

doi:10.1186/1471-2288-14-41

Cited by 426Statistical Methods in Clinical TrialsStatistical Methods and Bayesian InferenceStatistical Methods in Epidemiology

The statistical interpretation of pilot trials: should significance thresholds be reconsidered?

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Lee, Ellen C, Whitehead, Amy L, Jacques, Richard M, Julious, Steven A·2014·BMC Medical Research Methodology

DOI 10.1186/1471-2288-14-41PMC PMC3994566

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Abstract

BACKGROUND: In an evaluation of a new health technology, a pilot trial may be undertaken prior to a trial that makes a definitive assessment of benefit. The objective of pilot studies is to provide sufficient evidence that a larger definitive trial can be undertaken and, at times, to provide a preliminary assessment of benefit. METHODS: We describe significance thresholds, confidence intervals and surrogate markers in the context of pilot studies and how Bayesian methods can be used in pilot trials. We use a worked example to illustrate the issues raised. RESULTS: We show how significance levels other than the traditional 5% should be considered to provide preliminary evidence for efficacy and how estimation and confidence intervals should be the focus to provide an estimated range of possible treatment effects. We also illustrate how Bayesian methods could also assist in the early assessment of a health technology. CONCLUSIONS: We recommend that in pilot trials the focus should be on descriptive statistics and estimation, using confidence intervals, rather than formal hypothesis testing and that confidence intervals other than 95% confidence intervals, such as 85% or 75%, be used for the estimation. The confidence interval should then be interpreted with regards to the minimum clinically important difference. We also recommend that Bayesian methods be used to assist in the interpretation of pilot trials. Surrogate endpoints can also be used in pilot trials but they must reliably predict the overall effect on the clinical outcome.

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Lee et al. reported that type 1 error levels other than the traditional 5% could be considered to provide preliminary evidence for efficacy, but concluded that a confidence interval approach is preferable.
“Lee et al. [14] also reported how type 1 error levels other than the traditional 5% could be considered to provide preliminary evidence for efficacy, although they did stop short of recommending doing this by concluding that a confidence interval approach is preferable.”
From Determining sample size for progression criteria for pragmatic pilot RCTs: the hypothesis test strikes back! (2021) · cites this paper as [14]
Pilot trials are underpowered to produce effects significant at conventional levels.
“such pilot trials are underpowered to produce effects significant at conventional levels (Lee, Whitehead, Jacques, & Julious, 2014).”
From The role of sleep dysfunction in the occurrence of delusions and hallucinations: A systematic review (2015) · cites this paper as Lee, Whitehead, Jacques, & Julious, 2014
This pilot RCT aimed to enroll 60 participants and was understood to be underpowered.
“This pilot RCT aimed to enroll 60 participants. As a pilot study, it was understood to be underpowered (54).”
From EMPOWER: A Multi-Site Pilot Trial to Reduce Distress in Surrogate Decision-Makers in the ICU (2024) · cites this paper as [54]

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Authors: Lee, E. C., Whitehead, A. L., Jacques, R. M., & Julious, S. A.
Affiliations: University of Sheffield (GB)
Corresponding author: Julious, Steven A
ORCID: Lee, Ellen C
Whitehead, Amy L
Jacques, Richard M
Julious, Steven A
Venue: BMC Medical Research Methodology
Publisher: Springer Science and Business Media LLC
Published: 2014-03-20
Volume: 14
Issue: 1
Pages: 41-41
ISSN: 1471-2288 (ISSN-L)
DOI: 10.1186/1471-2288-14-41
PMC: PMC3994566
OpenAlex: W2108052506
Cited by: 423
References: 31
Citations by year: 2026: 26 · 2025: 60 · 2024: 50 · 2023: 59 · 2022: 52 · 2021: 40 · 2020: 34 · 2019: 30 · 2018: 31 · 2017: 16 · 2016: 14 · 2015: 9 · 2014: 2
FWCI: 14.45
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
www.springer.com/tdm (unspecified)
Locations: BMC Medical Research Methodology (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
ePrints Soton (University of Southampton) (acceptedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords: pilot trial, significance threshold, confidence intervals, Bayesian analysis, surrogate endpoints, minimal clinically important difference, health technology assessment, treatment effect estimation, hypothesis testing
MeSH terms: Bayes Theorem, Data Interpretation, Statistical, Humans, Leg Ulcer, Pilot Projects, Research Design, Biomarkers, Confidence Intervals, Treatment Outcome

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The statistical interpretation of pilot trials: should significance thresholds be reconsidered?

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