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Article: Non-parametric overdose control for dose finding in drug combination trials

TitleNon-parametric overdose control for dose finding in drug combination trials
Authors
KeywordsBayesian model selection
Drug combination
Loss function
Maximum tolerated dose contour
Non‐parametric design
Issue Date2019
PublisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9876
Citation
Journal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68 n. 4, p. 1111-1130 How to Cite?
AbstractWith the emergence of novel targeted anticancer agents, drug combinations have been recognized as cutting edge development in oncology. However, limited attention has been paid to overdose control in the existing drug combination dose finding methods which simultaneously find a set of maximum tolerated dose (MTD) combinations. To enhance patient safety, we develop the multiple‐agent non‐parametric overdose control (MANOC) design for identifying the MTD combination in phase I drug combination trials. By minimizing an asymmetric loss function, we control the probability of overdosing in a local region of the current dose combination. We further extend the MANOC design to identify the MTD contour by conducting a sequence of single‐agent subtrials with the dose level of one agent fixed. Simulation studies are conducted to investigate the performance of the designs proposed. Although the MANOC design can prevent patients from being allocated to overtoxic dose levels, its accuracy and efficiency in dose finding remain competitive with existing methods. As an illustration, the MANOC design is applied to a phase I clinical trial for identifying the MTD combinations of buparlisib and trametinib.
Persistent Identifierhttp://hdl.handle.net/10722/279511
ISSN
2021 Impact Factor: 1.680
2020 SCImago Journal Rankings: 1.205
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLAM, CK-
dc.contributor.authorLIN, R-
dc.contributor.authorYin, G-
dc.date.accessioned2019-11-01T07:18:46Z-
dc.date.available2019-11-01T07:18:46Z-
dc.date.issued2019-
dc.identifier.citationJournal of the Royal Statistical Society: Series C (Applied Statistics), 2019, v. 68 n. 4, p. 1111-1130-
dc.identifier.issn0035-9254-
dc.identifier.urihttp://hdl.handle.net/10722/279511-
dc.description.abstractWith the emergence of novel targeted anticancer agents, drug combinations have been recognized as cutting edge development in oncology. However, limited attention has been paid to overdose control in the existing drug combination dose finding methods which simultaneously find a set of maximum tolerated dose (MTD) combinations. To enhance patient safety, we develop the multiple‐agent non‐parametric overdose control (MANOC) design for identifying the MTD combination in phase I drug combination trials. By minimizing an asymmetric loss function, we control the probability of overdosing in a local region of the current dose combination. We further extend the MANOC design to identify the MTD contour by conducting a sequence of single‐agent subtrials with the dose level of one agent fixed. Simulation studies are conducted to investigate the performance of the designs proposed. Although the MANOC design can prevent patients from being allocated to overtoxic dose levels, its accuracy and efficiency in dose finding remain competitive with existing methods. As an illustration, the MANOC design is applied to a phase I clinical trial for identifying the MTD combinations of buparlisib and trametinib.-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9876-
dc.relation.ispartofJournal of the Royal Statistical Society: Series C (Applied Statistics)-
dc.subjectBayesian model selection-
dc.subjectDrug combination-
dc.subjectLoss function-
dc.subjectMaximum tolerated dose contour-
dc.subjectNon‐parametric design-
dc.titleNon-parametric overdose control for dose finding in drug combination trials-
dc.typeArticle-
dc.identifier.emailYin, G: gyin@hku.hk-
dc.identifier.authorityYin, G=rp00831-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/rssc.12349-
dc.identifier.scopuseid_2-s2.0-85063664180-
dc.identifier.hkuros308630-
dc.identifier.volume68-
dc.identifier.issue4-
dc.identifier.spage1111-
dc.identifier.epage1130-
dc.identifier.isiWOS:000475984600013-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0035-9254-

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