Evidence map›Paper›PMID 40551266›Full record

ArticlePilot and feasibility studies2025

Sample size justification in feasibility studies: moving beyond published guidance.

Robert Montgomery

Abstract readLetter
In one paragraph

Article in Pilot and feasibility studies, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

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  3. Contemporary clinical trials communications · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Robert MontgomeryDepartment of Biostatistics and Data Science, University of Kansas Medical Center, 3901 Rainbow Blvd., Kansas City, 66160, KS, USA. rmontgomery@kumc.edu.ORCID http://orcid.org/0000-0002-1423-0590

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pilot and feasibility studies are crucial for determining whether follow-up trials should be conducted. To be effective, these studies need to be properly designed and have large enough samples to make correct decisions about proceeding to a future trial at a high rate. However, there is significantly less clarity about best practices concerning sample size justifications compared to larger randomized controlled trials which are usually justified by power analyses. This has led to many feasibility studies justifying sample sizes based on pragmatic reasons (e.g., the ability to complete) or on published guidance and various rules of thumb. We argue that feasibility studies should be designed for, or at least report relevant operating characteristics, specifically, the probability of determining a future trial will be feasible when it is and the probability of determining a trial will be feasible when it is not and that sample size justifications should be based on these operating characteristics whenever possible. If relevant operating characteristics for a study are not reported, it is difficult to know whether the evidence from these trials can be used to claim a future trial would be feasible. In this paper, we review common methods for determining samples sizes in feasibility studies, report a narrative review of recently published feasibility studies and use two case-studies to highlight core issues we believe exist in the current design and reporting of these studies. Finally, we provide some suggestions that we believe will enhance the sample size justifications and overall effectiveness of these important trials.

Indexed as

FeasibilityGuidancePilot studyRules of thumbSample size

Identifiers

PMID40551266
PMCPMC12186404

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.