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dc.contributor.authorVillar, Sofía Sen
dc.contributor.authorBowden, Jacken
dc.contributor.authorWason, Jamesen
dc.date.accessioned2018-02-06T18:09:37Z
dc.date.available2018-02-06T18:09:37Z
dc.date.issued2018-03en
dc.identifier.issn1539-1604
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/271741
dc.description.abstractResponse-adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients - referred to as patient drift . This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude in order to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the two-armed and the multi-armed case. We further propose a RAR design for multi-armed clinical trials, which is computationally effcient and robust to several time trends considered.
dc.format.mediumPrint-Electronicen
dc.languageengen
dc.publisherWiley-Blackwell
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectHumansen
dc.subjectTreatment Outcomeen
dc.subjectPatient Selectionen
dc.subjectTime Factorsen
dc.subjectRandomized Controlled Trials as Topicen
dc.subjectStandard of Careen
dc.titleResponse-adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?en
dc.typeArticle
prism.endingPage197
prism.issueIdentifier2en
prism.publicationDate2018en
prism.publicationNamePharmaceutical statisticsen
prism.startingPage182
prism.volume17en
dc.identifier.doi10.17863/CAM.18732
dcterms.dateAccepted2017-11-07en
rioxxterms.versionofrecord10.1002/pst.1845en
rioxxterms.versionVoR*
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/en
rioxxterms.licenseref.startdate2018-03en
dc.contributor.orcidVillar, Sofía S [0000-0001-7755-2637]
dc.contributor.orcidWason, James [0000-0002-4691-126X]
dc.identifier.eissn1539-1612
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idMRC (unknown)
pubs.funder-project-idBiometrika Trust (unknown)
pubs.funder-project-idMRC (MR/N028171/1)
pubs.funder-project-idMedical Research Council (MR/J004979/1)
cam.orpheus.successThu Jan 30 12:58:18 GMT 2020 - The item has an open VoR version.*
rioxxterms.freetoread.startdate2100-01-01


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International