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dc.contributor.authorBofill Roig, Marta
dc.contributor.authorGómez Melis, Guadalupe
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.date.accessioned2018-02-23T09:09:58Z
dc.date.available2018-10-12T00:30:30Z
dc.date.issued2017-10-12
dc.identifier.citationBofill, M., Gomez, G. Selection of composite binary endpoints in clinical trials. "Biometrical journal", 12 Octubre 2017.
dc.identifier.issn0323-3847
dc.identifier.urihttp://hdl.handle.net/2117/114394
dc.descriptionThis is the peer reviewed version of the following article: Bofill, M., Gomez, G. Selection of composite binary endpoints in clinical trials. "Biometrical journal", 12 Octubre 2017, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/bimj.201600229/pdf. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
dc.description.abstractThe choice of a primary endpoint is an important issue when designing a clinical trial. It is common to use composite endpoints as a primary endpoint because it increases the number of observed events, captures more information and is expected to increase the power. However, combining events that have no similar clinical importance and have different treatment effects makes the interpretation of the results cumbersome and might reduce the power of the corresponding tests. Gómez and Lagakos proposed the ARE (asymptotic relative efficiency) method to choose between a composite or one of its components as primary endpoint comparing the efficacy of a treatment based on the times to each of these endpoints. The aim of this paper is to expand the ARE method to binary endpoints. We show that the ARE method depends on six parameters including the degree of association between components, event proportion, and effect of therapy given by the corresponding odds ratio of the single endpoints. A case study is presented to illustrate the methodology. We conclude with efficient guidelines for discerning which could be the best suited primary endpoint given anticipated parameters.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Simulació
dc.subject.lcshNumerical analysis--Simulation methods
dc.subject.lcshNumerical analysis
dc.subject.otherAsymptotic relative efficiency
dc.subject.otherBinary endpoint
dc.subject.otherClinical trial
dc.subject.otherComposite endpoint
dc.subject.otherTreatment effects
dc.titleSelection of composite binary endpoints in clinical trials
dc.typeArticle
dc.subject.lemacAnàlisi numèrica -- Processament de dades
dc.subject.lemacAnàlisi numèrica
dc.contributor.groupUniversitat Politècnica de Catalunya. GRBIO - Grup de Recerca en Bioestadística i Bioinformàtica
dc.identifier.doi10.1002/bimj.201600229
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::65 Numerical analysis::65C Probabilistic methods, simulation and stochastic differential equations
dc.subject.amsClassificació AMS::65 Numerical analysis::65K Mathematical programming, optimization and variational techniques
dc.relation.publisherversionhttp://onlinelibrary.wiley.com/doi/10.1002/bimj.201600229/abstract
dc.rights.accessOpen Access
local.identifier.drac21589304
dc.description.versionPostprint (author's final draft)
local.citation.authorBofill, M.; Gomez, G.
local.citation.publicationNameBiometrical journal


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