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Article: Design and sample size for evaluating combinations of drugs of linear and loglinear dose-response curves

TitleDesign and sample size for evaluating combinations of drugs of linear and loglinear dose-response curves
Authors
KeywordsAdditive action
Dose-effect
Experimental design
F-Test
Interaction index
Synergism
Uniform design
Issue Date2009
PublisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10543406.asp
Citation
Journal of Biopharmaceutical Statistics, 2009, v. 19 n. 4, p. 625-640 How to Cite?
AbstractThe study of drug combinations has become important in drug development due to its potential for efficacy at lower, less toxic doses and the need to move new therapies rapidly into clinical trials. The goal is to identify which combinations are additive, synergistic, or antagonistic. Although there exists statistical framework for finding doses and sample sizes needed to detect departure from additivity, e.g., the power maximized F-test, different classes of drugs of different does-response shapes require different derivation for calculating sample size and finding doses. Motivated by two anticancer combination studies that we are involved with, this article proposes dose-finding and sample size method for detecting departures from additivity of two drugs with linear and log-linear single dose-response curves. The first study involves combination of two drugs, where one single drug dose-response curve is linear and the other is log-linear. The second study involves combinations of drugs whose single drug dose-response curves are linear. The experiment had been planned with the common fixed ratio design before we were consulted, but the resulting data missed the synergistic combinations. However, the experiment based on the proposed design was able to identify the synergistic combinations as anticipated. Thus we shall summarize the analysis of the data collected according to the proposed design and discuss why the commonly used fixed ratio method failed and the implications of the proposed method for other combination studies.
Persistent Identifierhttp://hdl.handle.net/10722/172467
ISSN
2021 Impact Factor: 1.503
2020 SCImago Journal Rankings: 0.557
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorFang, HBen_US
dc.contributor.authorTian, GLen_US
dc.contributor.authorLi, Wen_US
dc.contributor.authorTan, Men_US
dc.date.accessioned2012-10-30T06:22:40Z-
dc.date.available2012-10-30T06:22:40Z-
dc.date.issued2009en_US
dc.identifier.citationJournal of Biopharmaceutical Statistics, 2009, v. 19 n. 4, p. 625-640en_US
dc.identifier.issn1054-3406en_US
dc.identifier.urihttp://hdl.handle.net/10722/172467-
dc.description.abstractThe study of drug combinations has become important in drug development due to its potential for efficacy at lower, less toxic doses and the need to move new therapies rapidly into clinical trials. The goal is to identify which combinations are additive, synergistic, or antagonistic. Although there exists statistical framework for finding doses and sample sizes needed to detect departure from additivity, e.g., the power maximized F-test, different classes of drugs of different does-response shapes require different derivation for calculating sample size and finding doses. Motivated by two anticancer combination studies that we are involved with, this article proposes dose-finding and sample size method for detecting departures from additivity of two drugs with linear and log-linear single dose-response curves. The first study involves combination of two drugs, where one single drug dose-response curve is linear and the other is log-linear. The second study involves combinations of drugs whose single drug dose-response curves are linear. The experiment had been planned with the common fixed ratio design before we were consulted, but the resulting data missed the synergistic combinations. However, the experiment based on the proposed design was able to identify the synergistic combinations as anticipated. Thus we shall summarize the analysis of the data collected according to the proposed design and discuss why the commonly used fixed ratio method failed and the implications of the proposed method for other combination studies.en_US
dc.languageengen_US
dc.publisherTaylor & Francis Inc. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10543406.aspen_US
dc.relation.ispartofJournal of Biopharmaceutical Statisticsen_US
dc.subjectAdditive action-
dc.subjectDose-effect-
dc.subjectExperimental design-
dc.subjectF-Test-
dc.subjectInteraction index-
dc.subjectSynergism-
dc.subjectUniform design-
dc.subject.meshAnalysis Of Varianceen_US
dc.subject.meshAntineoplastic Agents - Pharmacology - Toxicityen_US
dc.subject.meshCell Line, Tumoren_US
dc.subject.meshCell Survival - Drug Effectsen_US
dc.subject.meshData Interpretation, Statisticalen_US
dc.subject.meshDose-Response Relationship, Drugen_US
dc.subject.meshDrug Synergismen_US
dc.subject.meshHumansen_US
dc.subject.meshLinear Modelsen_US
dc.subject.meshModels, Statisticalen_US
dc.subject.meshResearch Design - Statistics & Numerical Dataen_US
dc.subject.meshSample Sizeen_US
dc.titleDesign and sample size for evaluating combinations of drugs of linear and loglinear dose-response curvesen_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.doi10.1080/10543400902964019en_US
dc.identifier.pmid20183430-
dc.identifier.scopuseid_2-s2.0-70449642897en_US
dc.identifier.hkuros163563-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-70449642897&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume19en_US
dc.identifier.issue4en_US
dc.identifier.spage625en_US
dc.identifier.epage640en_US
dc.identifier.isiWOS:000273633600005-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridFang, HB=7402543028en_US
dc.identifier.scopusauthoridTian, GL=25621549400en_US
dc.identifier.scopusauthoridLi, W=26643105800en_US
dc.identifier.scopusauthoridTan, M=7401464906en_US
dc.identifier.citeulike5446046-
dc.identifier.issnl1054-3406-

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