Literature DB >> 12933525

The validation of surrogate endpoints in meta-analyses of randomized experiments.

M Buyse1, G Molenberghs, T Burzykowski, D Renard, H Geys.   

Abstract

The validation of surrogate endpoints has been studied by Prentice (1989). He presented a definition as well as a set of criteria, which are equivalent only if the surrogate and true endpoints are binary. Freedman et al. (1992) supplemented these criteria with the so-called 'proportion explained'. Buyse and Molenberghs (1998) proposed replacing the proportion explained by two quantities: (1) the relative effect linking the effect of treatment on both endpoints and (2) an individual-level measure of agreement between both endpoints. The latter quantity carries over when data are available on several randomized trials, while the former can be extended to be a trial-level measure of agreement between the effects of treatment of both endpoints. This approach suggests a new method for the validation of surrogate endpoints, and naturally leads to the prediction of the effect of treatment upon the true endpoint, given its observed effect upon the surrogate endpoint. These ideas are illustrated using data from two sets of multicenter trials: one comparing chemotherapy regimens for patients with advanced ovarian cancer, the other comparing interferon-alpha with placebo for patients with age-related macular degeneration.

Entities:  

Year:  2000        PMID: 12933525     DOI: 10.1093/biostatistics/1.1.49

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  138 in total

1.  Principal stratification in causal inference.

Authors:  Constantine E Frangakis; Donald B Rubin
Journal:  Biometrics       Date:  2002-03       Impact factor: 2.571

2.  Comparing biomarkers as principal surrogate endpoints.

Authors:  Ying Huang; Peter B Gilbert
Journal:  Biometrics       Date:  2011-04-22       Impact factor: 2.571

Review 3.  Is blood pressure reduction a valid surrogate endpoint for stroke prevention? An analysis incorporating a systematic review of randomised controlled trials, a by-trial weighted errors-in-variables regression, the surrogate threshold effect (STE) and the Biomarker-Surrogacy (BioSurrogate) Evaluation Schema (BSES).

Authors:  Marissa N Lassere; Kent R Johnson; Michal Schiff; David Rees
Journal:  BMC Med Res Methodol       Date:  2012-03-12       Impact factor: 4.615

4.  Meta-analysis of the association between progression-free survival and overall survival in metastatic colorectal cancer.

Authors:  Costel Chirila; Dawn Odom; Giovanna Devercelli; Shahnaz Khan; Bintu N Sherif; James A Kaye; István Molnár; Beth Sherrill
Journal:  Int J Colorectal Dis       Date:  2011-11-12       Impact factor: 2.571

5.  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 6.  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

7.  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

8.  Predicting treatment effect from surrogate endpoints and historical trials: an extrapolation involving probabilities of a binary outcome or survival to a specific time.

Authors:  Stuart G Baker; Daniel J Sargent; Marc Buyse; Tomasz Burzykowski
Journal:  Biometrics       Date:  2011-08-13       Impact factor: 2.571

9.  Statistical controversies in clinical research: an initial evaluation of a surrogate end point using a single randomized clinical trial and the Prentice criteria.

Authors:  G Heller
Journal:  Ann Oncol       Date:  2015-08-07       Impact factor: 32.976

Review 10.  Modelling and simulation in the development and use of anti-cancer agents: an underused tool?

Authors:  Ferdinand Rombout; Leon Aarons; Mats Karlsson; Anthony Man; France Mentré; Peter Nygren; Amy Racine; Hans Schaefer; Jean-Louis Steimer; Iñaki Troconiz; Achiel van Peer
Journal:  J Pharmacokinet Pharmacodyn       Date:  2004-12       Impact factor: 2.745

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