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dc.contributor.authorRamon Marsal, Josep
dc.contributor.authorFerreira González, Ignacio
dc.contributor.authorBertrán, Sandra
dc.contributor.authorRibera, Aida
dc.contributor.authorPermanyer-Miralda, Gaietà
dc.contributor.authorGarcia Dorado, Antonio David
dc.contributor.authorGómez Melis, Guadalupe
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.date.accessioned2017-11-20T15:21:50Z
dc.date.available2018-05-01T00:30:41Z
dc.date.issued2017-04-10
dc.identifier.citationRamon, J., Ferreira González, I., Bertrán, S., Ribera, A., Permanyer-Miralda, G., Garcia-Dorado, D., Gomez, G. The use of a binary composite endpoint and sample size requirement: influence of endpoints overlap. "American journal of epidemiology", 10 Abril 2017, vol. 185, núm. 9, p. 832-841.
dc.identifier.issn0002-9262
dc.identifier.urihttp://hdl.handle.net/2117/110928
dc.description.abstractAlthough composite endpoints (CE) are common in clinical trials, the impact of the relationship between the components of a binary CE on the sample size requirement (SSR) has not been addressed. We performed a computational study considering 2 treatments and a CE with 2 components: the relevant endpoint (RE) and the additional endpoint (AE). We assessed the strength of the components’ interrelation by the degree of relative overlap between them, which was stratified into 5 groups. Within each stratum, SSR was computed for multiple scenarios by varying the events proportion and the effect of the therapy. A lower SSR using CE was defined as the best scenario for using the CE. In 25 of 66 scenarios the degree of relative overlap determined the benefit of using CE instead of the RE. Adding an AE with greater effect than the RE leads to lower SSR using the CE regardless of the AE proportion and the relative overlap. The influence of overlapping decreases when the effect on RE increases. Adding an AE with lower effect than the RE constitutes the most uncertain situation. In summary, the interrelationship between CE components, assessed by the relative overlap, can help to define the SSR in specific situations and it should be considered for SSR computation.
dc.format.extent10 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa
dc.subject.otherassociation measures
dc.subject.otherbinary endpoints
dc.subject.othercomposite endpoint
dc.subject.othercorrelated endpoints
dc.subject.otheroutcome assessment
dc.subject.othersample size
dc.titleThe use of a binary composite endpoint and sample size requirement: influence of endpoints overlap
dc.typeArticle
dc.contributor.groupUniversitat Politècnica de Catalunya. GRBIO - Grup de Recerca en Bioestadística i Bioinformàtica
dc.identifier.doi10.1093/aje/kww105
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::90 Operations research, mathematical programming
dc.relation.publisherversionhttps://academic.oup.com/aje/article-abstract/doi/10.1093/aje/kww105/3573392/The-Use-of-a-Binary-Composite-Endpoint-and-Sample?redirectedFrom=fulltext
dc.rights.accessOpen Access
drac.iddocument20330093
dc.description.versionPostprint (published version)
upcommons.citation.authorRamon, J., Ferreira González, I., Bertrán, S., Ribera, A., Permanyer-Miralda, G., Garcia-Dorado, D., Gomez, G.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameAmerican journal of epidemiology
upcommons.citation.volume185
upcommons.citation.number9
upcommons.citation.startingPage832
upcommons.citation.endingPage841


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