Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/2250
Title: | Validation of surrogate markers in multiple randomized clinical trials with repeated measurements: Canonical correlation approach | Authors: | ALONSO ABAD, Ariel GEYS, Helena MOLENBERGHS, Geert Kenward, Michael G. VANGENEUGDEN, Tony |
Issue Date: | 2004 | Publisher: | BLACKWELL PUBLISHING LTD | Source: | BIOMETRICS, 60(4). p. 845-853 | Abstract: | Part of the recent literature on the evaluation of biomarkers as surrogate endpoints starts from a multitrial context, which leads to a definition of validity in terms of the quality of both trial-level and individual-level association between the surrogate and true endpoints (Buyse et al., 2000, Biostatistics 1, 49-67). These authors concentrated on cross-sectional continuous responses. However, in many randomized clinical studies, repeated measurements are encountered on either or both endpoints. A challenge in this setting is the formulation of a simple and meaningful concept of "surrogacy." Alonso et al. (2003, Biometrical Journal 45, 931-945) proposed the variance reduction factor (VRF) to evaluate surrogacy at the individual level. They also showed how and when this concept should be extended to study surrogacy at the trial level. Here, we approach the problem from the natural canonical correlation perspective. We define a class of canonical correlation functions that can be used to study surrogacy at the trial and individual level. We show that the VRF and the R-2 measure defined by Buyse et al. (2000) follow as special cases. Simulations are conducted to evaluate the performance of different members of this family. The methodology is illustrated on data from a meta-analysis of five clinical trials comparing antipsychotic agents for the treatment of chronic schizophrenia. | Notes: | Transnatl Univ Limburg, Limburgs Univ Ctr, Ctr Stat, B-3590 Diepenbeek, Belgium. Univ London London Sch Hyg & Trop Med, Med Stat Unit, London WC1E 7HT, England. Johnson & Johnson Pharmaceut Res & Dev, B-2340 Beerse, Belgium.Alonso, A, Transnatl Univ Limburg, Limburgs Univ Ctr, Ctr Stat, Univ Campus, B-3590 Diepenbeek, Belgium.ariel.alonso@luc.ac.be | Keywords: | bivariate longitudinal data; canonical correlations; randomized clinical trials; surrogate marker; validation;bivariate longitudinal data; canonical correlations; randomized clinical trials; surrogate marker; validation | Document URI: | http://hdl.handle.net/1942/2250 | ISSN: | 0006-341X | e-ISSN: | 1541-0420 | DOI: | 10.1111/j.0006-341X.2004.00239.x | ISI #: | 000225939300001 | Rights: | BIOMETRICS | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2006 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Alonso_et_al-2004-Biometrics.pdf Restricted Access | Published version | 155.07 kB | Adobe PDF | View/Open Request a copy |
SCOPUSTM
Citations
21
checked on Sep 5, 2020
WEB OF SCIENCETM
Citations
22
checked on Oct 14, 2024
Page view(s)
60
checked on Sep 7, 2022
Download(s)
44
checked on Sep 7, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.