Literature DB >> 17447943

Surrogate marker evaluation from an information theory perspective.

Ariel Alonso1, Geert Molenberghs.   

Abstract

The last 20 years have seen lots of work in the area of surrogate marker validation, partly devoted to frame the evaluation in a multitrial framework, leading to definitions in terms of the quality of trial- and individual-level association between a potential surrogate and a true endpoint (Buyse et al., 2000, Biostatistics 1, 49-67). A drawback is that different settings have led to different measures at the individual level. Here, we use information theory to create a unified framework, leading to a definition of surrogacy with an intuitive interpretation, offering interpretational advantages, and applicable in a wide range of situations. Our method provides a better insight into the chances of finding a good surrogate endpoint in a given situation. We further show that some of the previous proposals follow as special cases of our method. We illustrate our methodology using data from a clinical study in psychiatry.

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Year:  2007        PMID: 17447943     DOI: 10.1111/j.1541-0420.2006.00634.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  14 in total

1.  A unified procedure for meta-analytic evaluation of surrogate end points in randomized clinical trials.

Authors:  James Y Dai; James P Hughes
Journal:  Biostatistics       Date:  2012-03-06       Impact factor: 5.899

Review 2.  Biomarkers and surrogate end points--the challenge of statistical validation.

Authors:  Marc Buyse; Daniel J Sargent; Axel Grothey; Alastair Matheson; Aimery de Gramont
Journal:  Nat Rev Clin Oncol       Date:  2010-04-06       Impact factor: 66.675

3.  An information-theoretic approach to surrogate-marker evaluation with failure time endpoints.

Authors:  Assam Pryseley; Abel Tilahun; Ariel Alonso; Geert Molenberghs
Journal:  Lifetime Data Anal       Date:  2010-09-28       Impact factor: 1.588

4.  Considerations for development of surrogate endpoints for antifracture efficacy of new treatments in osteoporosis: a perspective.

Authors:  Mary L Bouxsein; Pierre D Delmas
Journal:  J Bone Miner Res       Date:  2008-08       Impact factor: 6.741

5.  Center-Within-Trial Versus Trial-Level Evaluation of Surrogate Endpoints.

Authors:  Lindsay A Renfro; Qian Shi; Yuan Xue; Junlong Li; Hongwei Shang; Daniel J Sargent
Journal:  Comput Stat Data Anal       Date:  2014-10-01       Impact factor: 1.681

6.  Evaluating the Proportion of Treatment Effect Explained by a Continuous Surrogate Marker in Logistic or Probit Regression Models.

Authors:  Jie Huang; Bin Huang
Journal:  Stat Biopharm Res       Date:  2010-05-01       Impact factor: 1.452

7.  Causal assessment of surrogacy in a meta-analysis of colorectal cancer trials.

Authors:  Yun Li; Jeremy M G Taylor; Michael R Elliott; Daniel J Sargent
Journal:  Biostatistics       Date:  2011-01-20       Impact factor: 5.899

Review 8.  Meta-analysis for the evaluation of surrogate endpoints in cancer clinical trials.

Authors:  Qian Shi; Daniel J Sargent
Journal:  Int J Clin Oncol       Date:  2009-04-24       Impact factor: 3.402

9.  A bayesian approach to surrogacy assessment using principal stratification in clinical trials.

Authors:  Yun Li; Jeremy M G Taylor; Michael R Elliott
Journal:  Biometrics       Date:  2009-08-10       Impact factor: 2.571

10.  Differences in symptom expression between unipolar and bipolar spectrum depression: Results from a nationally representative sample using item response theory (IRT).

Authors:  Nicolas Hoertel; Carlos Blanco; Hugo Peyre; Melanie M Wall; Kibby McMahon; Philip Gorwood; Cédric Lemogne; Frédéric Limosin
Journal:  J Affect Disord       Date:  2016-06-15       Impact factor: 4.839

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