Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/11049
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMOLENBERGHS, Geert-
dc.contributor.authorBURZYKOWSKI, Tomasz-
dc.contributor.authorALONSO ABAD, Ariel-
dc.contributor.authorASSAM NKOUIBERT, Pryseley-
dc.contributor.authorTilahun, Abel-
dc.contributor.authorBUYSE, Marc-
dc.date.accessioned2010-08-03T12:10:48Z-
dc.date.availableNO_RESTRICTION-
dc.date.available2010-08-03T12:10:48Z-
dc.date.issued2010-
dc.identifier.citationSTATISTICAL METHODS IN MEDICAL RESEARCH, 19 (3) p. 205-236-
dc.identifier.issn0962-2802-
dc.identifier.urihttp://hdl.handle.net/1942/11049-
dc.description.abstractFor a number of reasons, surrogate endpoints are considered instead of the so-called true endpoint in clinical studies, especially when such endpoints can be measured earlier, and/or with less burden for patient and experimenter. Surrogate endpoints may occur more frequently than their standard counterparts. For these reasons, it is not surprising that the use of surrogate endpoints in clinical practice is increasing. Building on the seminal work of Prentice(1) and Freedman et al.,(2) Buyse et al.(3) framed the evaluation exercise within a meta-analytic setting, in an effort to overcome difficulties that necessarily surround evaluation efforts based on a single trial. In this article, we review the meta-analytic approach for continuous outcomes, discuss extensions to non-normal and longitudinal settings, as well as proposals to unify the somewhat disparate collection of validation measures currently on the market. Implications for design and for predicting the effect of treatment in a new trial, based on the surrogate, are discussed. A case study in schizophrenia is analysed.-
dc.description.sponsorshipThe authors gratefully acknowledge support from Belgian IUAP/PAI network 'Statistical Techniques and Modelling for Complex Substantive Questions with Complex Data'.-
dc.language.isoen-
dc.publisherSAGE PUBLICATIONS LTD-
dc.rights© The Author(s), 2010. Reprints and permissions-
dc.subject.otherhierarchical model; information theory; likelihood reduction factor; metaanalysis; random-effects model; surrogate endpoint; surrogate threshold effect-
dc.titleA unified framework for the evaluation of surrogate endpoints in mental-health clinical trials-
dc.typeJournal Contribution-
dc.identifier.epage236-
dc.identifier.issue3-
dc.identifier.spage205-
dc.identifier.volume19-
local.format.pages32-
local.bibliographicCitation.jcatA1-
dc.description.notes[Molenberghs, Geert] Hasselt Univ, Ctr Stat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert] Katholieke Univ Leuven, Leuven, Belgium. [Buyse, Marc] Int Inst Drug Dev, Ottignies, Belgium. geert.molenberghs@uhasselt.be-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1177/0962280209105015-
dc.identifier.isi000279354100002-
item.validationecoom 2011-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
item.fullcitationMOLENBERGHS, Geert; BURZYKOWSKI, Tomasz; ALONSO ABAD, Ariel; ASSAM NKOUIBERT, Pryseley; Tilahun, Abel & BUYSE, Marc (2010) A unified framework for the evaluation of surrogate endpoints in mental-health clinical trials. In: STATISTICAL METHODS IN MEDICAL RESEARCH, 19 (3) p. 205-236.-
item.contributorMOLENBERGHS, Geert-
item.contributorBURZYKOWSKI, Tomasz-
item.contributorALONSO ABAD, Ariel-
item.contributorASSAM NKOUIBERT, Pryseley-
item.contributorTilahun, Abel-
item.contributorBUYSE, Marc-
crisitem.journal.issn0962-2802-
crisitem.journal.eissn1477-0334-
Appears in Collections:Research publications
Files in This Item:
File Description SizeFormat 
surrog33b[1].pdfPeer-reviewed author version302.48 kBAdobe PDFView/Open
molenberghs2009.pdf
  Restricted Access
Published version289.35 kBAdobe PDFView/Open    Request a copy
Show simple item record

SCOPUSTM   
Citations

13
checked on Sep 2, 2020

WEB OF SCIENCETM
Citations

14
checked on Apr 30, 2024

Page view(s)

66
checked on Sep 7, 2022

Download(s)

284
checked on Sep 7, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.