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Article: Bayesian model averaging continual reassessment method in phase I clinical trials

TitleBayesian model averaging continual reassessment method in phase I clinical trials
Authors
KeywordsAdaptive design
Bayesian inference
Maximum tolerated dose
Model selection
Posterior model probability
Robustness
Toxicity probability
Issue Date2009
PublisherAmerican Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main
Citation
Journal Of The American Statistical Association, 2009, v. 104 n. 487, p. 954-968 How to Cite?
AbstractThe continual reassessment method (CRM) is a popular dose-finding design for phase I clinical trials. This method requires that practitioners prespecify the toxicity probability at each dose. Such prespecification can be arbitrary, and different specifications of toxicity probabilities may lead to very different design properties. To overcome the arbitrariness and further enhance the robustness of the design, we propose using multiple parallel CRM models, each with a different set of prespecified toxicity probabilities. In the Bayesian paradigm, we assign a discrete probability mass to each CRM model as the prior model probability. The posterior probabilities of toxicity can be estimated by the Bayesian model averaging (BMA) approach. Dose escalation or deescalation is determined by comparing the target toxicity rate and the BMA estimates of the dose toxicity probabilities. We examine the properties of the BMA-CRM approach through extensive simulation studies, and also compare this new method and its variants with the original CRM. The results demonstrate that our BMA-CRM is competitive and robust, and eliminates the arbitrariness of the prespecification of toxicity probabilities. © 2009 American Statistical Association.
Persistent Identifierhttp://hdl.handle.net/10722/139729
ISSN
2015 Impact Factor: 1.725
2015 SCImago Journal Rankings: 3.447
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYin, Gen_HK
dc.contributor.authorYuan, Yen_HK
dc.date.accessioned2011-09-23T05:54:49Z-
dc.date.available2011-09-23T05:54:49Z-
dc.date.issued2009en_HK
dc.identifier.citationJournal Of The American Statistical Association, 2009, v. 104 n. 487, p. 954-968en_HK
dc.identifier.issn0162-1459en_HK
dc.identifier.urihttp://hdl.handle.net/10722/139729-
dc.description.abstractThe continual reassessment method (CRM) is a popular dose-finding design for phase I clinical trials. This method requires that practitioners prespecify the toxicity probability at each dose. Such prespecification can be arbitrary, and different specifications of toxicity probabilities may lead to very different design properties. To overcome the arbitrariness and further enhance the robustness of the design, we propose using multiple parallel CRM models, each with a different set of prespecified toxicity probabilities. In the Bayesian paradigm, we assign a discrete probability mass to each CRM model as the prior model probability. The posterior probabilities of toxicity can be estimated by the Bayesian model averaging (BMA) approach. Dose escalation or deescalation is determined by comparing the target toxicity rate and the BMA estimates of the dose toxicity probabilities. We examine the properties of the BMA-CRM approach through extensive simulation studies, and also compare this new method and its variants with the original CRM. The results demonstrate that our BMA-CRM is competitive and robust, and eliminates the arbitrariness of the prespecification of toxicity probabilities. © 2009 American Statistical Association.en_HK
dc.languageengen_US
dc.publisherAmerican Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=mainen_HK
dc.relation.ispartofJournal of the American Statistical Associationen_HK
dc.subjectAdaptive designen_HK
dc.subjectBayesian inferenceen_HK
dc.subjectMaximum tolerated doseen_HK
dc.subjectModel selectionen_HK
dc.subjectPosterior model probabilityen_HK
dc.subjectRobustnessen_HK
dc.subjectToxicity probabilityen_HK
dc.titleBayesian model averaging continual reassessment method in phase I clinical trialsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0162-1459&volume=104&issue=487&spage=954&epage=968&date=2009&atitle=Bayesian+model+averaging+continual+reassessment+method+in+phase+I+clinical+trials-
dc.identifier.emailYin, G: gyin@hku.hken_HK
dc.identifier.authorityYin, G=rp00831en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1198/jasa.2009.ap08425en_HK
dc.identifier.scopuseid_2-s2.0-70349776681en_HK
dc.identifier.hkuros195700en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70349776681&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume104en_HK
dc.identifier.issue487en_HK
dc.identifier.spage954en_HK
dc.identifier.epage968en_HK
dc.identifier.eissn1537-274X-
dc.identifier.isiWOS:000270916100007-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYin, G=8725807500en_HK
dc.identifier.scopusauthoridYuan, Y=55176482000en_HK

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