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Article: Bayesian phase I/II adaptively randomized oncology trials with combined drugs

TitleBayesian phase I/II adaptively randomized oncology trials with combined drugs
Authors
KeywordsAdaptive randomization
Dose finding
Drug combination
Issue Date2011
PublisherInstitute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aoas/
Citation
Annals of Applied Statistics, 2011, v. 5 n. 2A, p. 924-942 How to Cite?
AbstractWe propose a new integrated phase I/II trial design to identify the most efficacious dose combination that also satisfies certain safety requirements for drug-combination trials. We first take a Bayesian copula-type model for dose finding in phase I. After identifying a set of admissible doses, we immediately move the entire set forward to phase II. We propose a novel adaptive randomization scheme to favor assigning patients to more efficacious dose-combination arms. Our adaptive randomization scheme takes into account both the point estimate and variability of efficacy. By using a moving reference to compare the relative efficacy among treatment arms, our method achieves a high resolution to distinguish different arms. We also consider groupwise adaptive randomization when efficacy is late-onset. We conduct extensive simulation studies to examine the operating characteristics of the proposed design, and illustrate our method using a phase I/II melanoma clinical trial.
Persistent Identifierhttp://hdl.handle.net/10722/139720
ISSN
2023 Impact Factor: 1.3
2023 SCImago Journal Rankings: 0.954
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYuan, Yen_US
dc.contributor.authorYin, Gen_US
dc.date.accessioned2011-09-23T05:54:46Z-
dc.date.available2011-09-23T05:54:46Z-
dc.date.issued2011en_US
dc.identifier.citationAnnals of Applied Statistics, 2011, v. 5 n. 2A, p. 924-942en_US
dc.identifier.issn1932-6157-
dc.identifier.urihttp://hdl.handle.net/10722/139720-
dc.description.abstractWe propose a new integrated phase I/II trial design to identify the most efficacious dose combination that also satisfies certain safety requirements for drug-combination trials. We first take a Bayesian copula-type model for dose finding in phase I. After identifying a set of admissible doses, we immediately move the entire set forward to phase II. We propose a novel adaptive randomization scheme to favor assigning patients to more efficacious dose-combination arms. Our adaptive randomization scheme takes into account both the point estimate and variability of efficacy. By using a moving reference to compare the relative efficacy among treatment arms, our method achieves a high resolution to distinguish different arms. We also consider groupwise adaptive randomization when efficacy is late-onset. We conduct extensive simulation studies to examine the operating characteristics of the proposed design, and illustrate our method using a phase I/II melanoma clinical trial.-
dc.languageengen_US
dc.publisherInstitute of Mathematical Statistics. The Journal's web site is located at http://www.imstat.org/aoas/en_US
dc.relation.ispartofAnnals of Applied Statisticsen_US
dc.subjectAdaptive randomization-
dc.subjectDose finding-
dc.subjectDrug combination-
dc.titleBayesian phase I/II adaptively randomized oncology trials with combined drugsen_US
dc.typeArticleen_US
dc.identifier.emailYin, G: gyin@hku.hken_US
dc.identifier.authorityYin, G=rp00831en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1214/10-AOAS433-
dc.identifier.scopuseid_2-s2.0-84873378000-
dc.identifier.hkuros195643en_US
dc.identifier.volume5en_US
dc.identifier.issue2Aen_US
dc.identifier.spage924en_US
dc.identifier.epage942en_US
dc.identifier.isiWOS:000295453300015-
dc.publisher.placeUnited States-
dc.identifier.issnl1932-6157-

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