Clinical Trials

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Register here to gain access to SAGE's 500+ Journals Online

Sign In to gain access to subscriptions and/or personal tools.
This Article
Right arrow Free Full Text (Free PDF) Free
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Pryseley, A.
Right arrow Articles by Molenberghs, G.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Pryseley, A.
Right arrow Articles by Molenberghs, G.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
Clinical Trials, Vol. 4, No. 6, 587-597 (2007)
DOI: 10.1177/1740774507084979

Information-theory based surrogate marker evaluation from several randomized clinical trials with continuous true and binary surrogate endpoints

Assam Pryseley

Hasselt University, Center for Statistics, Agoralaan 1, B3590 Diepenbeek, Belgium

Abel Tilahun

Hasselt University, Center for Statistics, Agoralaan 1, B3590 Diepenbeek, Belgium

Ariel Alonso

Hasselt University, Center for Statistics, Agoralaan 1, B3590 Diepenbeek, Belgium

Geert Molenberghs

Hasselt University, Center for Statistics, Agoralaan 1, B3590 Diepenbeek, Belgium, geert.molenberghs{at}uhasselt.be

Background Surrogate endpoints potentially reduce the duration and/or increase the amount of information available in a study, thereby diminishing patient burden and cost. They may also increase the effectiveness and reliability of research, through beneficial impact on noncompliance and missingness.

Purpose In this article, we review the meta-analytic approach of Buyse et al. (2000) and its extension to mixed continuous and binary endpoints by Molenberghs Geys, and Buyse (2001).

Methods An information-theoretic alternative, based on Alonso and Molenberghs (2007a) is proposed. The method is evaluated using simulations and application to data from an ophthalmologic trial, with lines of vision lost at 6 months as candidate surrogate endpoints for lines of vision lost at 12 months. The method is implemented as an R function.

Results The information-theoretic approach is based on solid theory, easy to apply, and enjoys elegant properties. While the information-theoretic approach appears to be somewhat biased downwards, this is due to fact that it operates at explicitly observed outcomes, without the need for unobserved, latent scales. This is a desirable property.

Limitations While easy-to-use and implement, the theoretical foundation of the information-theory approach is more mathematical. It produces some bias for small to moderate trial/center sizes, and hence is recommended primarily for sufficiently large trials.

Conclusions Since the meta-analytic framework can be computationally extremely expensive, the information-theoretic approach of Alonso and Molenberghs (2007a) is a viable alternative. For the ophthalmologic case study, the conclusion is that the lines of vision lost at sixth month do have some, but not overwhelming promise as a surrogate endpoint. Clinical Trials 2007; 4: 587—597. http://ctj.sagepub.com


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?