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Article: Experimental design and sample size determination for testing synergism in drug combination studies based on uniform measures

TitleExperimental design and sample size determination for testing synergism in drug combination studies based on uniform measures
Authors
Issue Date2003
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/
Citation
Statistics In Medicine, 2003, v. 22 n. 13, p. 2091-2100 How to Cite?
AbstractIn anticancer drug development, the combined use of two drugs is an important strategy to achieve greater therapeutic success. Often combination studies are performed in animal (mostly mice) models before clinical trials are conducted. These experiments on mice are costly, especially with combination studies. However, experimental designs and sample size derivations for the joint action of drugs are not currently available except for a few cases where strong model assumptions are made. For example, Abdelbasit and Plackett proposed an optimal design assuming that the dose-response relationship follows some specified linear models. Tallarida et al. derived a design by fixing the mixture ratio and used a t-test to detect the simple similar action. The issue is that in reality we usually do not have enough information on the joint action of the two compounds before experiment and to understand their joint action is exactly our study goal. In this paper, we first propose a novel non-parametric model that does not impose such strong assumptions on the joint action. We then propose an experimental design for the joint action using uniform measure in this non-parametric model. This design is optimal in the sense that it reduces the variability in modelling synergy while allocating the doses to minimize the number of experimental units and to extract maximum information on the joint action of the compounds. Based on this design, we propose a robust F-test to detect departures from the simple similar action of two compounds and a method to determine sample sizes that are economically feasible. We illustrate the method with a study of the joint action of two new anticancer agents: temozolomide and irinotecan. Copyright © 2003 John Wiley & Sons, Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/172403
ISSN
2015 Impact Factor: 1.533
2015 SCImago Journal Rankings: 1.811
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorTan, Men_US
dc.contributor.authorFang, HBen_US
dc.contributor.authorTian, GLen_US
dc.contributor.authorHoughton, PJen_US
dc.date.accessioned2012-10-30T06:22:21Z-
dc.date.available2012-10-30T06:22:21Z-
dc.date.issued2003en_US
dc.identifier.citationStatistics In Medicine, 2003, v. 22 n. 13, p. 2091-2100en_US
dc.identifier.issn0277-6715en_US
dc.identifier.urihttp://hdl.handle.net/10722/172403-
dc.description.abstractIn anticancer drug development, the combined use of two drugs is an important strategy to achieve greater therapeutic success. Often combination studies are performed in animal (mostly mice) models before clinical trials are conducted. These experiments on mice are costly, especially with combination studies. However, experimental designs and sample size derivations for the joint action of drugs are not currently available except for a few cases where strong model assumptions are made. For example, Abdelbasit and Plackett proposed an optimal design assuming that the dose-response relationship follows some specified linear models. Tallarida et al. derived a design by fixing the mixture ratio and used a t-test to detect the simple similar action. The issue is that in reality we usually do not have enough information on the joint action of the two compounds before experiment and to understand their joint action is exactly our study goal. In this paper, we first propose a novel non-parametric model that does not impose such strong assumptions on the joint action. We then propose an experimental design for the joint action using uniform measure in this non-parametric model. This design is optimal in the sense that it reduces the variability in modelling synergy while allocating the doses to minimize the number of experimental units and to extract maximum information on the joint action of the compounds. Based on this design, we propose a robust F-test to detect departures from the simple similar action of two compounds and a method to determine sample sizes that are economically feasible. We illustrate the method with a study of the joint action of two new anticancer agents: temozolomide and irinotecan. Copyright © 2003 John Wiley & Sons, Ltd.en_US
dc.languageengen_US
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/en_US
dc.relation.ispartofStatistics in Medicineen_US
dc.subject.meshAnimalsen_US
dc.subject.meshAntineoplastic Combined Chemotherapy Protocols - Administration & Dosage - Pharmacologyen_US
dc.subject.meshCamptothecin - Administration & Dosage - Analogs & Derivatives - Pharmacologyen_US
dc.subject.meshDacarbazine - Administration & Dosage - Analogs & Derivatives - Pharmacologyen_US
dc.subject.meshDrug Synergismen_US
dc.subject.meshMiceen_US
dc.subject.meshModels, Biologicalen_US
dc.subject.meshModels, Statisticalen_US
dc.subject.meshNeoplasms, Experimental - Drug Therapyen_US
dc.subject.meshResearch Designen_US
dc.subject.meshSample Sizeen_US
dc.subject.meshStatistics, Nonparametricen_US
dc.titleExperimental design and sample size determination for testing synergism in drug combination studies based on uniform measuresen_US
dc.typeArticleen_US
dc.identifier.emailTian, GL: gltian@hku.hken_US
dc.identifier.authorityTian, GL=rp00789en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1002/sim.1467en_US
dc.identifier.pmid12820275-
dc.identifier.scopuseid_2-s2.0-0038726249en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0038726249&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume22en_US
dc.identifier.issue13en_US
dc.identifier.spage2091en_US
dc.identifier.epage2100en_US
dc.identifier.isiWOS:000183770100001-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridTan, M=7401464681en_US
dc.identifier.scopusauthoridFang, HB=7402543028en_US
dc.identifier.scopusauthoridTian, GL=25621549400en_US
dc.identifier.scopusauthoridHoughton, PJ=36044344200en_US
dc.identifier.citeulike3883753-

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