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dc.contributor.authorMozgunov, Pavel
dc.contributor.authorKnight, Rochelle
dc.contributor.authorBarnett, Helen
dc.contributor.authorJaki, Thomas
dc.date.accessioned2021-01-07T02:07:56Z
dc.date.available2021-01-07T02:07:56Z
dc.date.issued2021-01-05
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/315816
dc.description.abstractThere is growing interest in Phase I dose-finding studies studying several doses of more than one agent simultaneously. A number of combination dose-finding designs were recently proposed to guide escalation/de-escalation decisions during the trials. The majority of these proposals are model-based: a parametric combination-toxicity relationship is fitted as data accumulates. Various parameter shapes were considered but the unifying theme for many of these is that typically between 4 and 6 parameters are to be estimated. While more parameters allow for more flexible modelling of the combination-toxicity relationship, this is a challenging estimation problem given the typically small sample size in Phase I trials of between 20 and 60 patients. These concerns gave raise to an ongoing debate whether including more parameters into combination-toxicity model leads to more accurate combination selection. In this work, we extensively study two variants of a 4-parameter logistic model with reduced number of parameters to investigate the effect of modelling assumptions. A framework to calibrate the prior distributions for a given parametric model is proposed to allow for fair comparisons. Via a comprehensive simulation study, we have found that the inclusion of the interaction parameter between two compounds does not provide any benefit in terms of the accuracy of selection, on average, but is found to result in fewer patients allocated to the target combination during the trial.
dc.languageen
dc.publisherMDPI
dc.subjectdose-escalation
dc.subjectcombination study
dc.subjectmodelling assumption
dc.subjectinteraction
dc.titleUsing an Interaction Parameter in Model-Based Phase I Trials for Combination Treatments? A Simulation Study
dc.typeArticle
dc.date.updated2021-01-07T02:07:55Z
prism.issueIdentifier1
prism.publicationNameInternational Journal of Environmental Research and Public Health
prism.volume18
dc.identifier.doi10.17863/CAM.62925
dcterms.dateAccepted2020-12-31
rioxxterms.versionofrecord10.3390/ijerph18010345
rioxxterms.versionVoR
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidMozgunov, Pavel [0000-0001-6810-0284]
dc.contributor.orcidJaki, Thomas [0000-0002-1096-188X]
dc.identifier.eissn1660-4601
pubs.funder-project-idNational Institute for Health Research (NIHR300576, NIHR-SRF-2015-08-001)
pubs.funder-project-idMedical Research Council (MC_UU_0002/14)


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