Literature DB >> 17825025

Quantifying the effect of the surrogate marker by information gain.

Yongming Qu1, Michael Case.   

Abstract

Statistical validation of a surrogate marker has been studied for more than a decade. Recently, Alonso et al. (2004, Biometrics 60, 724-728) proposed a quantity called the likelihood reduction factor (LRF) to evaluate the validity of a surrogate marker. However, as pointed out in the present article, the LRF may not correctly validate a surrogate marker. Therefore, a new quantity, the proportion of information gain (PIG) using the Kullback-Leibler information, is proposed. Simulations show that under some model assumptions, the PIG precisely reflects the role of a surrogate marker.

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Year:  2007        PMID: 17825025     DOI: 10.1111/j.1541-0420.2007.00852_1.x

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


  8 in total

1.  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

2.  Use of the likelihood reduction factor in a path analysis framework to quantify surrogacy in clinical trials.

Authors:  Katherine Bloore; Yang Song; Howard Cabral; Joseph Massaro; Michael LaValley
Journal:  Stat Med       Date:  2021-09-21       Impact factor: 2.373

3.  Estimation of the proportion of treatment effect explained by a high-dimensional surrogate.

Authors:  Ruixuan Rachel Zhou; Sihai Dave Zhao; Layla Parast
Journal:  Stat Med       Date:  2022-02-21       Impact factor: 2.497

4.  Short-Term Relapse Quantitation as a Fully Surrogate Endpoint for Long-Term Sustained Progression of Disability in RRMS Patients Treated with Natalizumab.

Authors:  Y C Wang; A Sandrock; J R Richert; L Meyerson; X Miao
Journal:  Neurol Res Int       Date:  2011-12-26

5.  Measuring Surrogacy in Clinical Research: With an application to studying surrogate markers for HIV Treatment-as-Prevention.

Authors:  Rui Zhuang; Ying Qing Chen
Journal:  Stat Biosci       Date:  2019-06-04

6.  Developing retinal biomarkers of neurological disease: an analytical perspective.

Authors:  Ian J C MacCormick; Gabriela Czanner; Brian Faragher
Journal:  Biomark Med       Date:  2015       Impact factor: 2.851

7.  Assessing correlates of protection in vaccine trials: statistical solutions in the context of high vaccine efficacy.

Authors:  Andrea Callegaro; Fabian Tibaldi
Journal:  BMC Med Res Methodol       Date:  2019-03-06       Impact factor: 4.615

Review 8.  Informed decision-making: Statistical methodology for surrogacy evaluation and its role in licensing and reimbursement assessments.

Authors:  Christopher J Weir; Rod S Taylor
Journal:  Pharm Stat       Date:  2022-07       Impact factor: 1.234

  8 in total

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