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dc.contributor.authorLee, Kimen
dc.contributor.authorWason, Jamesen
dc.date.accessioned2018-10-10T17:31:02Z
dc.date.available2018-10-10T17:31:02Z
dc.date.issued2019-03en
dc.identifier.issn0378-3758
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/283587
dc.description.abstractPrecision medicine, aka stratified/ personalized medicine, is becoming more pronounced in the medical field due to advancement in computational ability to learn about patient genomic backgrounds. A biomaker, i.e. a type of biological process indicator, is often used in precision medicine to classify patient population into several subgroups. The aim of precision medicine is to tailor treatment regimes for different patient subgroups who suffer from the same disease. A multi-arm design could be conducted to explore the effect of treatment regimes on different biomarker subgroups. However, if treatments work only on certain subgroups, which is often the case, enrolling all patient subgroups in a confirmatory trial would increase the burden of a study. Having observed a phase II trial, we propose a design framework for finding an optimal design that could be implemented in a phase III study or a confirmatory trial. We consider two elements in our approach: Bayesian data analysis of observed data, and design of experiments. The first tool selects subgroups and treatments to be enrolled in the future trial whereas the second tool provides an optimal treatment randomization scheme for each selected/ enrolled subgroups. Considering two independent treatments and two independent biomarkers, we illustrate our approach using simulation studies. We demonstrate efficiency gain, i.e. high probability of recommending truly effective treatments in the right subgroup, of the optimal design found by our framework over a randomized controlled trial and a biomarker-treatment linked trial.
dc.format.mediumPrinten
dc.languageengen
dc.publisherElsevier
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleDesign of experiments for a confirmatory trial of precision medicine.en
dc.typeArticle
prism.endingPage187
prism.publicationDate2019en
prism.publicationNameJournal of statistical planning and inferenceen
prism.startingPage179
prism.volume199en
dc.identifier.doi10.17863/CAM.30949
dcterms.dateAccepted2018-06-16en
rioxxterms.versionofrecord10.1016/j.jspi.2018.06.004en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2019-03en
dc.contributor.orcidWason, James [0000-0002-4691-126X]
dc.identifier.eissn1873-1171
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idMRC (MR/N028171/1)
pubs.funder-project-idMRC (unknown)


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