Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/23702
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dc.contributor.authorKent, D. M.en
dc.contributor.authorRothwell, P. M.en
dc.contributor.authorIoannidis, J. P.en
dc.contributor.authorAltman, D. G.en
dc.contributor.authorHayward, R. A.en
dc.date.accessioned2015-11-24T19:35:24Z-
dc.date.available2015-11-24T19:35:24Z-
dc.identifier.issn1745-6215-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/23702-
dc.rightsDefault Licence-
dc.subjectClinical Trials as Topic/*methods/*standards/statistics & numerical dataen
dc.subjectEvidence-Based Medicine/*standards/*statistics & numerical dataen
dc.subjectHumansen
dc.subjectMultivariate Analysisen
dc.subjectReproducibility of Resultsen
dc.subjectRisk Assessment/methods/standards/statistics & numerical dataen
dc.subjectRisk Factorsen
dc.subjectTherapeutics/*statistics & numerical dataen
dc.titleAssessing and reporting heterogeneity in treatment effects in clinical trials: a proposalen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primary10.1186/1745-6215-11-85-
heal.identifier.secondaryhttp://www.ncbi.nlm.nih.gov/pubmed/20704705-
heal.identifier.secondaryhttp://www.trialsjournal.com/content/pdf/1745-6215-11-85.pdf-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικήςel
heal.publicationDate2010-
heal.abstractMounting evidence suggests that there is frequently considerable variation in the risk of the outcome of interest in clinical trial populations. These differences in risk will often cause clinically important heterogeneity in treatment effects (HTE) across the trial population, such that the balance between treatment risks and benefits may differ substantially between large identifiable patient subgroups; the "average" benefit observed in the summary result may even be non-representative of the treatment effect for a typical patient in the trial. Conventional subgroup analyses, which examine whether specific patient characteristics modify the effects of treatment, are usually unable to detect even large variations in treatment benefit (and harm) across risk groups because they do not account for the fact that patients have multiple characteristics simultaneously that affect the likelihood of treatment benefit. Based upon recent evidence on optimal statistical approaches to assessing HTE, we propose a framework that prioritizes the analysis and reporting of multivariate risk-based HTE and suggests that other subgroup analyses should be explicitly labeled either as primary subgroup analyses (well-motivated by prior evidence and intended to produce clinically actionable results) or secondary (exploratory) subgroup analyses (performed to inform future research). A standardized and transparent approach to HTE assessment and reporting could substantially improve clinical trial utility and interpretability.en
heal.journalNameTrialsen
heal.journalTypepeer-reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) - ΙΑΤ

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