Cited by 123Statistical Methods in Clinical TrialsMeta-analysis and systematic reviewsStatistical Methods in Epidemiology

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Should treatment effects be estimated in pilot and feasibility studies?

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Sim, Julius·2019·Pilot and Feasibility Studies

DOI 10.1186/s40814-019-0493-7PMC PMC6712606

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Abstract

BACKGROUND: Feasibility studies and external pilot studies are used increasingly to inform planning decisions related to a definitive randomized controlled trial. These studies can provide information on process measures, such as consent rates, treatment fidelity and compliance, and methods of outcome measurement. Additionally, they can provide initial parameter estimates for a sample size calculation, such as a standard deviation or the 'success' rate for a binary outcome in the control group. However, the issue of estimating treatment effects in pilot or feasibility studies is controversial. METHODOLOGICAL DISCUSSION: Between-group estimates of treatment effect from pilot studies are sometimes used to calculate the sample size for a main trial, alongside estimated standard deviations. However, whilst estimating a standard deviation is an empirical matter, a targeted treatment effect should be established in terms of clinical judgement, as a minimum important difference (MID), not through analysis of pilot data. Secondly, between-group effects measured in pilot studies are sometimes used to indicate the magnitude of an effect that might be obtained in a main trial, and a decision on progression made with reference to the associated confidence interval. Such estimates will be imprecise in typically small pilot studies and therefore do not allow a robust decision on a main trial; both a decision to proceed and a decision not to proceed may be made too readily. Thirdly, a within-group change might be estimated from a pilot or a feasibility study in a desire to assess the potential efficacy of a novel intervention prior to testing it in a main trial, but again such estimates are liable to be imprecise and do not allow sound causal inferences. CONCLUSION: Treatment effects calculated from pilot or feasibility studies should not be the basis of a sample size calculation for a main trial, as the MID to be detected should be based primarily on clinical judgement rather than statistics. Deciding on progression to a main trial based on these treatment effects is also misguided, as they will normally be imprecise, and may be biased if the pilot or feasibility study is unrepresentative of the main trial.

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Fig. 1 Estimated treatment effects, with 95% confidence intervals, reported for four outcomes by Sheehan et al. [25]. A difference in percentage improvement of 40% (indicated by the dashed horizontal reference line) was taken to be the minimum important differenceCC BY · PubMed Central

Fig. 2 Simulated data for 20 pilot studies (each n = 34) estimating an unknown ‘true’ treatment effect of 10, with a standard deviation of 20, and with an assumed minimum important difference of 4 (dashed horizontal reference line). Error bars are 95% confidence intervals, and the observed underlying standard deviations range from 12.6 to 24.8CC BY · PubMed Central

Fig. 3 Confidence intervals for the estimated treatment effect in study 18 (n = 34) in the simulated example, at varying confidence levels from 95 to 70%. The dashed horizontal reference line indicates the minimum important differenceCC BY · PubMed Central

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Additional file 1 of Pilot and feasibility trials in traditional Chinese medicine: a literature review of current practice
Li, G., Wu, D., Chen, X., Zeng, J., Li, Z., & Thabane, L. (2020) · Figshare · doi:10.6084/m9.figshare.12177828
Additional file 1 of A pilot and feasibility study of a randomized clinical trial testing a self-compassion intervention aimed to increase physical activity behaviour among people with prediabetes
Signore, A., Jung, M. E., Semenchuk, B. N., Kullman, S. M., Tefft, O., Webber, S., Ferguson, L. J., Kowalski, K. C., Fortier, M., McGavock, J., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19914936
Additional file 1 of Multimodal agility-based exercise training (MAT) versus strength and endurance training (SET) to improve multiple sclerosis-related fatigue and fatigability during inpatient rehabilitation: a randomized controlled pilot and feasibility study [ReFEx]
Wolf, F., Nielsen, J., Saliger, J., Hennecken, E., Kröber, P., Eschweiler, M., Folkerts, A.-K., Karbe, H., & Zimmer, P. (2023) · Figshare · doi:10.6084/m9.figshare.24454957
Additional file 1 of Determining sample size for progression criteria for pragmatic pilot RCTs: the hypothesis test strikes back!
Lewis, M., Bromley, K., Sutton, C., McCray, G., Myers, H. L., & Lancaster, G. A. (2021) · Figshare · doi:10.6084/m9.figshare.13710841
Additional file 2 of Early-stage studies to larger-scale trials: investigators’ perspectives on scaling-up childhood obesity interventions
von Klinggraeff, L., Dugger, R., Okely, A. D., Lubans, D., Jago, R., Burkart, S., Weaver, R. G., Armstrong, B., Pfledderer, C. D., & Beets, M. W. (2022) · Figshare · doi:10.6084/m9.figshare.19136116
Additional file 1 of A review of sample sizes for UK pilot and feasibility studies on the ISRCTN registry from 2013 to 2020
Totton, N., Lin, J., Julious, S., Chowdhury, M., & Brand, A. (2024) · Figshare · doi:10.6084/m9.figshare.26643079
Additional file 2 of The mysterious case of the disappearing pilot study: a review of publication bias in preliminary behavioral interventions presented at health behavior conferences
von Klinggraeff, L., Ramey, K. T., Pfledderer, C. D., Burkart, S. A., Armstrong, B., Weaver, R. G., & Beets, M. W. (2023) · Figshare · doi:10.6084/m9.figshare.23647454
Additional file 1 of Evaluating the impact of Community-Based Sociotherapy on social dignity in post-genocide Rwanda: study protocol for a cluster randomized controlled trial
Jansen, S., Niyonsenga, J., Ingabire, M. C., Jansen, A., Nzabonimpa, E., Ingabire, N., Kangabe, J., Sarabwe, E., Richters, A., Rutayisire, T., et al. (2023) · Figshare · doi:10.6084/m9.figshare.22599410
Additional file 1 of Early-stage studies to larger-scale trials: investigators’ perspectives on scaling-up childhood obesity interventions
von Klinggraeff, L., Dugger, R., Okely, A. D., Lubans, D., Jago, R., Burkart, S., Weaver, R. G., Armstrong, B., Pfledderer, C. D., & Beets, M. W. (2022) · Figshare · doi:10.6084/m9.figshare.19136113

Authors: Sim, J.
Affiliations: Keele University (GB)
Corresponding author: Sim, Julius
ORCID: Sim, Julius
Venue: Pilot and Feasibility Studies
Publisher: Springer Science and Business Media LLC
Published: 2019-08-28
Volume: 5
Issue: 1
Pages: 107-107
ISSN: 2055-5784 (ISSN-L)
DOI: 10.1186/s40814-019-0493-7
PMC: PMC6712606
OpenAlex: W2970940014
Cited by: 123
References: 31
Citations by year: 2026: 15 · 2025: 13 · 2024: 13 · 2023: 23 · 2022: 20 · 2021: 18 · 2020: 19 · 2019: 2
FWCI: 11.51
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (tdm)
creativecommons.org/licenses/by/4.0/ (vor)
Locations: Pilot and Feasibility Studies (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Keele Research Repository (Keele University) (submittedVersion, cc-by)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords: pilot study, feasibility study, treatment effect estimation, sample size determination, minimal clinically important difference, clinical judgment, trial planning, confidence intervals

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