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http://hdl.handle.net/1942/20492
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DC Field | Value | Language |
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dc.contributor.author | BUYSE, Marc | - |
dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | PAOLETTI, Xavier | - |
dc.contributor.author | Oba, Koji | - |
dc.contributor.author | ALONSO ABAD, Ariel | - |
dc.contributor.author | VAN DER ELST, Wim | - |
dc.contributor.author | BURZYKOWSKI, Tomasz | - |
dc.date.accessioned | 2016-02-04T10:16:03Z | - |
dc.date.available | 2016-02-04T10:16:03Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | BIOMETRICAL JOURNAL, 58 (1), p. 104-132 | - |
dc.identifier.issn | 0323-3847 | - |
dc.identifier.uri | http://hdl.handle.net/1942/20492 | - |
dc.description.abstract | A surrogate endpoint is intended to replace a clinical endpoint for the evaluation of new treatments when it can be measured more cheaply, more conveniently, more frequently, or earlier than that clinical endpoint. A surrogate endpoint is expected to predict clinical benefit, harm, or lack of these. Besides the biological plausibility of a surrogate, a quantitative assessment of the strength of evidence for surrogacy requires the demonstration of the prognostic value of the surrogate for the clinical outcome, and evidence that treatment effects on the surrogate reliably predict treatment effects on the clinical outcome. We focus on these two conditions, and outline the statistical approaches that have been proposed to assess the extent to which these conditions are fulfilled. When data are available from a single trial, one can assess the "individual level association" between the surrogate and the true endpoint. When data are available from several trials, one can additionally assess the "trial level association" between the treatment effect on the surrogate and the treatment effect on the true endpoint. In the latter case, the "surrogate threshold effect" can be estimated as the minimum effect on the surrogate endpoint that predicts a statistically significant effect on the clinical endpoint. All these concepts are discussed in the context of randomized clinical trials in oncology, and illustrated with two meta-analyses in gastric cancer. | - |
dc.description.sponsorship | The authors gratefully acknowledge support from IAP Research Network P7/06 of the Belgian Government (Belgian Science Policy). They thank the GASTRIC (Global Advanced/Adjuvant Stomach Tumor Research International Collaboration) Group for permission to use their data. The investigators who contributed to GASTRIC are listed in references (Oba et al., 2013; Paoletti et al., 2013; The GASTRIC Group, 2010, 2013). The GASTRIC Group data used in the present paper can be downloaded from the journal website for research purposes, under the conditions that (1) the research be scientifically appropriate, (2) the confidentiality of individual patient data be protected, (3) the results of the analyses be shared with the GASTRIC Group prior to public communication, (4) the source of data be fully acknowledged as above, and (5) resulting data and results be further shared with the research community. Software implementations for the methods described in this paper are available from www.ibiostat.be/software. | - |
dc.language.iso | en | - |
dc.publisher | WILEY-BLACKWELL | - |
dc.rights | © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim | - |
dc.subject.other | Individual level association; Surrogate endpoint; Surrogate threshold effect; Trial level association | - |
dc.subject.other | individual level association; surrogate endpoint; surrogate threshold effect; trial level association | - |
dc.title | Statistical evaluation of surrogate endpoints with examples from cancer clinical trials | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 132 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 104 | - |
dc.identifier.volume | 58 | - |
local.format.pages | 29 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | [Buyse, Marc] IDDI, Cambridge, MA 02138 USA. [Buyse, Marc; Molenberghs, Geert; Van der Elst, Wim; Burzykowski, Tomasz] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat I BioSt, B-3500 Hasselt, Belgium. [Molenberghs, Geert; Alonso, Ariel] Univ Leuven, KU Leuven, Interuniv Inst Biostat & Stat Bioinformat I BioSt, B-3000 Leuven, Belgium. [Paoletti, Xavier] Inst Curie, INSERM U900, Dept Biostat, F-75005 Paris, France. [Oba, Koji] Univ Tokyo, Grad Sch Med, Sch Publ Hlth, Dept Biostat,Bunkyo Ku, Tokyo 1130033, Japan. [Oba, Koji] Univ Tokyo, Interfac Initiat Informat Studies, Bunkyo Ku, Tokyo 1130033, Japan. [Burzykowski, Tomasz] IDDI, B-1340 Louvain La Neuve, Belgium. | - |
local.publisher.place | HOBOKEN | - |
local.type.refereed | Refereed | - |
local.type.specified | Review | - |
dc.identifier.doi | 10.1002/bimj.201400049 | - |
dc.identifier.isi | 000367731300008 | - |
item.fulltext | With Fulltext | - |
item.contributor | BUYSE, Marc | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | PAOLETTI, Xavier | - |
item.contributor | Oba, Koji | - |
item.contributor | ALONSO ABAD, Ariel | - |
item.contributor | VAN DER ELST, Wim | - |
item.contributor | BURZYKOWSKI, Tomasz | - |
item.accessRights | Restricted Access | - |
item.validation | ecoom 2017 | - |
item.fullcitation | BUYSE, Marc; MOLENBERGHS, Geert; PAOLETTI, Xavier; Oba, Koji; ALONSO ABAD, Ariel; VAN DER ELST, Wim & BURZYKOWSKI, Tomasz (2016) Statistical evaluation of surrogate endpoints with examples from cancer clinical trials. In: BIOMETRICAL JOURNAL, 58 (1), p. 104-132. | - |
crisitem.journal.issn | 0323-3847 | - |
crisitem.journal.eissn | 1521-4036 | - |
Appears in Collections: | Research publications |
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buyse 1.pdf Restricted Access | Published version | 526.71 kB | Adobe PDF | View/Open Request a copy |
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