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dc.contributor.authorBell, Melanie L
dc.contributor.authorWhitehead, Amy L
dc.contributor.authorJulious, Steven A
dc.date.accessioned2018-03-21T18:33:39Z
dc.date.available2018-03-21T18:33:39Z
dc.date.issued2018-01
dc.identifier.citationGuidance for using pilot studies to inform the design of intervention trials with continuous outcomes 2018, Volume 10:153 Clinical Epidemiologyen
dc.identifier.issn1179-1349
dc.identifier.pmid29403314
dc.identifier.doi10.2147/CLEP.S146397
dc.identifier.urihttp://hdl.handle.net/10150/627081
dc.description.abstractBackground: 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.
dc.description.sponsorshipNCI NIH HHS [P30 CA023074]en
dc.language.isoenen
dc.publisherDOVE MEDICAL PRESS LTDen
dc.relation.urlhttps://www.dovepress.com/guidance-for-using-pilot-studies-to-inform-the-design-of-intervention--peer-reviewed-article-CLEPen
dc.rights© 2018 Bell et al. This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms. php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License.en
dc.rights.urihttps://creativecommons.org/licenses/by-nc/3.0/
dc.subjectpiloten
dc.subjectfeasibilityen
dc.subjectsample sizeen
dc.subjectpoweren
dc.subjectrandomized controlled trialen
dc.subjectsensitivity analysisen
dc.titleGuidance for using pilot studies to inform the design of intervention trials with continuous outcomesen
dc.typeArticleen
dc.contributor.departmentUniv Arizona, Mel & Enid Zuckerman Coll Publ Hlth, Dept Epidemiol & Biostaten
dc.identifier.journalClinical Epidemiologyen
dc.description.noteOpen access journal.en
dc.description.noteUA Open Access Publishing Fund.
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en
dc.eprint.versionFinal published versionen
refterms.dateFOA2018-06-12T12:50:39Z
html.description.abstractBackground: 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.


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© 2018 Bell et al. This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms. php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License.
Except where otherwise noted, this item's license is described as © 2018 Bell et al. This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms. php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License.