Cited by 280Statistical Methods in Clinical TrialsStatistical Methods in EpidemiologyMeta-analysis and systematic reviews

Guidance for using pilot studies to inform the design of intervention trials with continuous outcomes

Open access
Bell, Melanie L, Whitehead, Amy L, Julious, Steven A·2018·Clinical Epidemiology

Abstract

BACKGROUND: A pilot study can be an important step in the assessment of an intervention by providing information to design the future definitive trial. Pilot studies can be used to estimate the recruitment and retention rates and population variance and to provide preliminary evidence of efficacy potential. However, estimation is poor because pilot studies are small, so sensitivity analyses for the main trial's sample size calculations should be undertaken. METHODS: We demonstrate how to carry out easy-to-perform sensitivity analysis for designing trials based on pilot data using an example. Furthermore, we introduce rules of thumb for the size of the pilot study so that the overall sample size, for both pilot and main trials, is minimized. RESULTS: The example illustrates how sample size estimates for the main trial can alter dramatically by plausibly varying assumptions. Required sample size for 90% power varied from 392 to 692 depending on assumptions. Some scenarios were not feasible based on the pilot study recruitment and retention rates. CONCLUSION: Pilot studies can be used to help design the main trial, but caution should be exercised. We recommend the use of sensitivity analyses to assess the robustness of the design assumptions for a main trial.

AI snapshot

Written from the paper’s full text.

TL;DR

Pilot studies can inform the design of definitive trials with continuous outcomes by estimating recruitment/retention, population variance, and preliminary efficacy potential, but their small size makes estimates imprecise. The paper recommends sensitivity analyses and stepped rules of thumb for pilot sample size, illustrated by an example where required main-trial sample size for 90% power ranged from 392 to 692 depending on assumptions.

Key findings

  • In the worked example, main-trial sample size for 90% power varied from 392 to 692 depending on assumptions about the SD and dropout rate; for 80% power, sample sizes ranged from 296 to 518.
  • The pilot example had a recruitment rate of 50% of eligible patients, at 25 recruitments per month, and 80% retention (40 of 50 participants completed all three assessments).
  • Based on a target standardized effect size of 4/14 = 0.29 for a 90% powered main trial, the stepped rules of thumb indicated 25 patients per arm for the pilot.
  • Feasibility assessment showed that recruiting over 1.5 years at 25 participants per month would enroll 450 participants, falling below several sample size estimates in the sensitivity analysis.

Methods

  • Methodological guidance paper with a worked example using a continuous outcome; it focuses on external pilot studies whose results are not combined with the main trial.
  • The example is a hypothetical two-arm RCT comparing a new supportive care regimen for cancer patients to usual care, with quality of life at 3 months measured by FACT-G; the pilot had 50 participants, with 100 potential participants, 70 referred, 60 eligible, and 50 agreeing to participate.
  • Main analysis demonstrates sample size sensitivity analyses varying the SD (pilot SD, upper 80% CI limit, literature estimate) and dropout rates (observed 20%, >5%, <5%), plus stepped rules of thumb for pilot sample size based on target effect size and future trial size.

Limitations

  • Stated: pilot studies are small, so effect size and SD estimates are imprecise; using a pilot study’s SD to design a future sample size has been shown to often result in an underpowered study, and preliminary efficacy evidence from a pilot should not be overstated.
  • Stated: sensitivity analyses are needed because sample size estimates can alter dramatically by plausibly varying assumptions, and some scenarios may not be feasible based on pilot recruitment and retention rates.
  • Evident from the text: the worked example is explicitly hypothetical (“Suppose…”), so its numerical results are illustrative rather than empirical findings from an actual pilot study.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.2147/clep.s146397

Cites

32 of 32 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 45 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    Required sample size for 90% power varied from 392 to 692 depending on assumptions.

    “Required sample size for 90% power varied from 392 to 692 depending on assumptions.”
    • Also stated in: § Sample size calculations and sensitivity analyses · plain
      “For 90% power, sample size ranges from 392 to 692.”
    Quote in the paperSubstantial claim
  • Findingown data

    The example illustrates how sample size estimates for the main trial can alter dramatically by plausibly varying assumptions.

    “The example illustrates how sample size estimates for the main trial can alter dramatically by plausibly varying assumptions.”
    • Also stated in: § Conclusion · boosted
      “The example demonstrated how main trial sample size estimates can vary dramatically by plausibly altering assumptions.”
    Quote in the paperSubstantial claim
  • Findingown data

    Some scenarios were not feasible based on the pilot study recruitment and retention rates.

    “Some scenarios were not feasible based on the pilot study recruitment and retention rates.”
    Quote in the paperNot a substantial claim
  • Findingown data

    For 80% power, sample sizes range from 296 to 518.

    “For 80% power, sample sizes range from 296 to 518.”
    Quote in the paperNot a substantial claim
  • Findingreasoning

    Using an MID estimate of four points and an SD of 14, the standardized effect size is 4/14=0.29.

    “Using an MID estimate of four points, and an SD of 14, the standardized effect size is 4/14=0.29.”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim. 23
  • May combine two claims. 15
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingreasoning

    If the pilot recruitment rate of 25 participants per month is a good estimate, then the study will be able to recruit and enroll 450 participants.

    “If the pilot recruitment rate of 25 participants per month is a good estimate, then the study will be able to recruit and enroll 450 participants.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data

    Of the 50 participants, 40 completed all three assessments; retention is 80%.

    “Of the 50 participants, 40 participants completed all three assessments; retention is 80%.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Findingreasoning

    The pilot study of 50 participants had a recruitment rate of 50% of eligible patients, at 25 recruitments per month.

    “This indicates a recruitment rate of 50% of eligible patients, at 25 recruitments per month.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Findingnone given

    The difference in quality of life between the arms at 3 months is estimated at 3.1 points, with 95% CI −1.8 to 8.0, and SD =11.2.

    “The difference in the quality of life between the arms at 3 months is estimated at 3.1 points, with 95% CI −1.8 to 8.0, and SD =11.2.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    450 participants falls below several of the estimates in Table 2.

    “This falls below several of the estimates in Table 2.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Hislop et al. identified seven approaches for determining the target effect size for an RCT and classified them as clinically important and/or realistic.

    “Hislop et al15 undertook a systematic review to identify seven approaches for determining the target effect size for an RCT and classified them as clinically important and/or realistic.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [15] Hislop J Adewuyi TE Vale LD Methods for specifying the target difference in a randomised controlled trial: the Difference ELicitation in TriAls (DELTA) systematic review PLoS Med 2014 11 5 e1001645 24824338 PMC4019477

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Most pilot studies do undertake hypothesis tests.

    “While some authors argue against carrying out hypothesis tests and assessing efficacy from pilots, even potential efficacy, most pilot studies do undertake hypothesis tests.6”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [6] Shanyinde M Pickering RM Weatherall M Questions asked and answered in pilot and feasibility randomized controlled trials BMC Med Res Methodol 2011 11 1 117 21846349 PMC3170294

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Pilot studies can be used to estimate recruitment and retention rates and population variance and to provide preliminary evidence of efficacy potential.

    “Pilot studies can be used to estimate the recruitment and retention rates and population variance and to provide preliminary evidence of efficacy potential.”
    • Also stated in: § Introduction · plain
      “To address this aim, there are a number of objectives for a pilot study including assessing recruitment and retention rates, obtaining estimates of parameters required for sample size calculation, and providing preliminary evidence of efficacy potential.3–6”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [3] Craig P Dieppe P Macintyre S Developing and evaluating complex interventions: the new Medical Research Council guidance BMJ 2008 337 a1655 18824488 PMC2769032

      Not checked in the free run.

    • cites [4] Lancaster G Campbell M Eldridge S Trials in primary care: statistical issues in the design, conduct and evaluation of complex interventions Stat Methods Med Res 2010 19 4 349 377 20442193

      Not checked in the free run.

    • cites [5] Cocks K Torgerson DJ Sample size calculations for pilot randomized trials: a confidence interval approach J Clin Epidemiol 2013 66 2 197 201 23195919

      Not checked in the free run.

    • cites [6] Shanyinde M Pickering RM Weatherall M Questions asked and answered in pilot and feasibility randomized controlled trials BMC Med Res Methodol 2011 11 1 117 21846349 PMC3170294

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Premisecitation

    A figure showing CIs, the MID, and the null value can be a helpful way of displaying pilot results.

    “A figure showing these CIs, the MID, and the null value can be a helpful way of displaying pilot results, by facilitating an assessment of both statistical significance and the potential for clinical significance.31”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [31] Bell ML Fiero MH Dhillon HM Bray VJ Vardy JL Statistical controversies in cancer research: using standardized effect size graphs to enhance interpretability of cancer-related clinical trials with patient-reported outcomes Ann Oncol 2017 28 8 1730 1733 28327975 PMC5834129

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Premisenone given

    Pilot trial results can inform target effect size, variance, and feasibility.

    “Pilot trial results can inform each of these elements.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Premisenone given

    The population SD is a key element of sample size estimation for continuous outcomes, and its estimation is one of the objectives for conducting a pilot study.

    “The population SD is another key element of sample size estimation for continuous outcomes, and its estimation is one of the objectives for conducting a pilot study.”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim.

    Premisecitation

    In the absence of a known MID for continuous outcomes, particularly patient-reported outcomes, a standardized effect size between 0.3 and 0.5 has been recommended.

    “In the absence of a known MID for continuous outcomes, particularly patient-reported outcomes, a standardized effect size15 between 0.3 and 0.5 has been recommended.17,18”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [15] Hislop J Adewuyi TE Vale LD Methods for specifying the target difference in a randomised controlled trial: the Difference ELicitation in TriAls (DELTA) systematic review PLoS Med 2014 11 5 e1001645 24824338 PMC4019477

      Not checked in the free run.

    • cites [17] King M A point of minimal important difference (MID): a critique of terminology and methods Expert Rev Pharmacoecon Outcomes Res 2011 11 2 171 184 21476819

      Not checked in the free run.

    • cites [18] Norman GR Sloan JA Wyrwich KW The truly remarkable universality of half a standard deviation: confirmation through another look Expert Rev Pharmacoecon Outcomes Res 2004 4 5 581 585 19807551

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Type I error and power are set independent of the pilot.

    “Factors such as type I error and power are set independent of the pilot and are discussed in detail elsewhere.7”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [7] Julious SA Sample sizes for clinical trials with normal data Stat Med 2004 23 12 1921 1986 15195324

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Many trials struggle to reach their sample size goal, which can result in trial extensions or failure to recruit to their prespecified sample size.

    “Many trials struggle to reach their sample size goal, which can result in trial extensions or failure to recruit to their prespecified sample size.10”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [10] Sully B Julious SA Nicholl J A reinvestigation of recruitment to randomised, controlled, multicenter trials: a review of trials funded by two UK funding agencies Trials 2013 14 166 23758961 PMC3691846

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Pilot trials are often small versions of the main trial, undertaken to test trial methods and procedures.

    “Pilot trials are often small versions of the main trial, undertaken to test trial methods and procedures.1,2”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [1] Thabane L Ma J Chu R A tutorial on pilot studies: the what, why and how BMC Med Res Methodol 2010 10 1 20053272 PMC2824145

      Not checked in the free run.

    • cites [2] Arain M Campbell MJ Cooper CL Lancaster GA What is a pilot or feasibility study? A review of current practice and editorial policy BMC Med Res Methodol 2010 10 67 20637084 PMC2912920

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Objectives for a pilot study include assessing recruitment and retention rates, obtaining estimates of parameters required for sample size calculation, and providing preliminary evidence of efficacy potential.

    “To address this aim, there are a number of objectives for a pilot study including assessing recruitment and retention rates, obtaining estimates of parameters required for sample size calculation, and providing preliminary evidence of efficacy potential.3–6”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [3] Craig P Dieppe P Macintyre S Developing and evaluating complex interventions: the new Medical Research Council guidance BMJ 2008 337 a1655 18824488 PMC2769032

      Not checked in the free run.

    • cites [4] Lancaster G Campbell M Eldridge S Trials in primary care: statistical issues in the design, conduct and evaluation of complex interventions Stat Methods Med Res 2010 19 4 349 377 20442193

      Not checked in the free run.

    • cites [5] Cocks K Torgerson DJ Sample size calculations for pilot randomized trials: a confidence interval approach J Clin Epidemiol 2013 66 2 197 201 23195919

      Not checked in the free run.

    • cites [6] Shanyinde M Pickering RM Weatherall M Questions asked and answered in pilot and feasibility randomized controlled trials BMC Med Res Methodol 2011 11 1 117 21846349 PMC3170294

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Using the pilot effect size to power the definitive trial is likely to mislead because estimation is poor due to the small sample size.

    “Although some researchers use the pilot effect size to power the definitive trial, this is a practice that should be avoided in general, as estimation is poor due to the small sample size, and is likely to mislead.19”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [19] Kraemer HC Mintz J Noda A Tinklenberg J Yesavage JA Caution regarding the use of pilot studies to guide power calculations for study proposals Arch Gen Psychiatry 2006 63 5 484 489 16651505

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Using significance levels other than the traditional 5% with corresponding CIs such as 85 and 75% in addition to 95% CIs can provide preliminary evidence for efficacy.

    “One approach for handling this uncertainty is to use significance levels other than the “traditional” 5% to provide preliminary evidence for efficacy, with corresponding CIs such as 85 and 75% in addition to 95% CIs.21”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [21] Lee EC Whitehead AL Jacques RM Julious SA The statistical interpretation of pilot trials: should significance thresholds be reconsidered? BMC Med Res Methodol 2014 14 1 41 24650044 PMC3994566

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Whitehead et al. proposed stepped rules of thumb for pilot studies based on the target effect size and the size of the future trial.

    “From this work, they proposed stepped rules of thumb for pilot studies based on the target effect size and the size of the future trial.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [27] Whitehead A Julious S Cooper C Campbell MJ Estimating the sample size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and main trial for a continuous outcome variable Stat Methods Med Res 2016 25 3 1057 1073 26092476 PMC4876429

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The decision to progress from a pilot trial to a main trial is generally made using feasibility estimates, as well as issues such as protocol nonadherence.

    “The decision to progress from a pilot trial to a main trial is generally made using feasibility estimates, as well as issues such as protocol nonadherence.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [11] Avery KNL Williamson PR Gamble C Informing efficient randomised controlled trials: exploration of challenges in developing progression criteria for internal pilot studies BMJ Open 2017 7 2 e013537 PMC5318608 28213598

      Not checked in the free run.

    • cites [14] Hampson LV Williamson PR Wilby MJ Jaki T A framework for prospectively defining progression rules for internal pilot studies monitoring recruitment Stat Methods Med Res Epub 2017 1 01 28589752

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    There are several rules of thumb for the size of a pilot study, ranging from 12 to 35 individuals per arm, and none of these guidelines account for the likely size of the future trial.

    “While there are several rules of thumb for the size of a pilot study, ranging from 12 to 35 individuals per arm,5,27 none of these guidelines account for the likely size of the future trial.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [5] Cocks K Torgerson DJ Sample size calculations for pilot randomized trials: a confidence interval approach J Clin Epidemiol 2013 66 2 197 201 23195919

      Not checked in the free run.

    • cites [27] Whitehead A Julious S Cooper C Campbell MJ Estimating the sample size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and main trial for a continuous outcome variable Stat Methods Med Res 2016 25 3 1057 1073 26092476 PMC4876429

      Not checked in the free run.

  • May combine two claims.

    Premisereasoning

    Traditional power calculations are inappropriate for pilot studies because the primary aim of a pilot study is not to test superiority of one treatment over the other.

    “Although traditional power calculations are inappropriate for pilot studies (since the primary aim of a pilot study is not to test superiority of one treatment over the other), a sample size justification is important.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Interpretationreasoning

    Pilot studies can aid in the design of future trials with continuous outcomes by providing estimates of population SD, evidence of potential for intervention effectiveness, and quantification of feasibility in the form of recruitment and retention rates.

    “We have illustrated how pilot studies can aid in the design of future trials with continuous outcomes by providing estimates of population SD, evidence of potential for intervention effectiveness, and quantification of feasibility in the form of recruitment and retention rates.”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim.

    Interpretationown data

    These rates will aid in estimating the main trial duration.

    “These rates will aid in estimating the main trial duration.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Premisecitation

    The estimated FACT-G MID is between three and six points and an SD estimate from the literature is 14 in similar populations.

    “They find that the estimated FACT-G MID is between three and six points29 and an SD estimate from the literature30 is 14 in similar populations.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [29] Webster K Cella D Yost K The functional assessment of chronic illness therapy (FACIT) measurement system: properties, applications, and interpretation Health Qual Life Outcomes 2003 1 79 14678568 PMC317391

      Not checked in the free run.

    • cites [30] Bell ML McKenzie JE Designing psycho-oncology randomised trials and cluster randomised trials: variance components and intra-cluster correlation of commonly used psychosocial measures Psychooncology 2013 22 8 1738 1747 23080401

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Sensitivity analyses can take the form of accounting for the uncertainty in estimation by calculating sample sizes based on a range of plausible SDs and retention/dropout rates.

    “Sensitivity analyses should also be performed in the design stage26 and can take the form of accounting for the uncertainty in estimation by calculating sample sizes based on a range of plausible SDs and retention/dropout rates.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [26] Lewis JA Statistical principles for clinical trials (ICH E9): an introductory note on an international guideline Stat Med 1999 18 15 1903 1942 10440877

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Premisecitation

    Sensitivity analyses are important to assess the robustness of study results to the assumptions made in the primary analysis.

    “Sensitivity analyses are important to assess the robustness of study results to the assumptions made in the primary analysis.25”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [25] Thabane L Mbuagbaw L Zhang S A tutorial on sensitivity analyses in clinical trials: the what, why, when and how BMC Med Res Methodol 2013 13 1 92 23855337 PMC3720188

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The objective of the pilot study to provide preliminary evidence of efficacy has been met.

    “Thus, the objective of the pilot study to provide preliminary evidence of efficacy has been met.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    For a future trial designed around a small effect, the number of patients per arm for the pilot study should be 25 for 90% power.

    “For example, if the future trial will be designed around a small effect, then the number of patients per arm for the pilot study should be 25 for 90% power.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [27] Whitehead A Julious S Cooper C Campbell MJ Estimating the sample size for a pilot randomised trial to minimise the overall trial sample size for the external pilot and main trial for a continuous outcome variable Stat Methods Med Res 2016 25 3 1057 1073 26092476 PMC4876429

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    A CONSORT extension for reporting results of pilot and feasibility studies gives detailed guidelines.

    “A CONSORT extension for reporting results of pilot and feasibility studies gives detailed guidelines.9”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [9] Eldridge SM Chan CL Campbell MJ CONSORT 2010 statement: extension to randomised pilot and feasibility trials BMJ 2016 355 i5239 27777223 PMC5076380

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    For a 90% powered main trial, they should use a sample size of 25 per arm for the pilot.

    “For a 90% powered main trial, they should use a sample size of 25 per arm for the pilot (Table 1).”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Browne suggested using the pilot study's upper limit of the 80% CI for the SD to calculate sample size in the subsequent trial.

    “Browne23 suggested using the pilot study’s upper limit of the 80% CI for the SD to calculate sample size in the subsequent trial.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [23] Browne RH On the use of a pilot sample for sample size determination Stat Med 1995 14 17 1933 1940 8532986

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Cocks and Torgerson recommend basing the pilot study size on the future trial's size, if the SD is known.

    “Cocks and Torgerson5 also recommend basing the pilot study size on the future trial’s size, if the SD is known.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [5] Cocks K Torgerson DJ Sample size calculations for pilot randomized trials: a confidence interval approach J Clin Epidemiol 2013 66 2 197 201 23195919

      Not checked in the free run.

33 of 33

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

  • Recruitment rate uses potential rather than eligible participants

    Minor

    The text says 60 participants met eligibility criteria and 50 agreed to participate. That is 83.3% of eligible participants, not the reported 50%; 50% is the proportion of the 100 potential participants.

    Reported 50 · recomputed 83.333333

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Authors
Bell, M. L., Whitehead, A. L., & Julious, S. A.
Affiliations
  • University of Arizona (US)
  • University of Sheffield (GB)
Corresponding author
Bell, Melanie L
Venue
Clinical Epidemiology
Published
2018-01
Volume
Volume 10
Pages
153-157
ISSN
1179-1349 (ISSN-L)
OpenAlex
W2783709266
Cited by
280
References
32
Citations by year
2026: 37 · 2025: 52 · 2024: 22 · 2023: 48 · 2022: 43 · 2021: 37 · 2020: 26 · 2019: 12 · 2018: 3
FWCI
16.18
Type
journal article
Language
en
Open access
Locations
  • Clinical Epidemiology (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
  • ePrints Soton (University of Southampton) (acceptedVersion)
  • UA Campus Repository (The University of Arizona) (acceptedVersion, cc-by-nc)
  • Dove Medical Press (Taylor and Francis Group) (submittedVersion, cc-by-nc)
Funders
  • University of Southampton
  • National Cancer Institute (P30CA023074)
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
pilot study, trial design, sample size determination, sensitivity analysis, continuous outcomes, population variance estimation

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