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journal contribution
posted on 2024-03-26, 17:11authored bySylwia Bujkiewicz, John R. Thompson, R. D. Riley, Keith R. Abrams
A number of meta-analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate
meta-analytical methods can be used to predict the treatment effect for the final outcome from the treatment
effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect
estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include
multiple surrogate endpoints with the potential benefit of reducing the uncertainty when making predictions. In
this Bayesian multivariate meta-analytic framework, the between-study variability is modelled in a formulation
of a product of normal univariate distributions. This formulation is particularly convenient for including multiple
surrogate endpoints and flexible for modelling the outcomes which can be surrogate endpoints to the final outcome
and potentially to one another. Two models are proposed, first using an unstructured between-study covariance
matrix by assuming the treatment effects on all outcomes are correlated and second using a structured between-
study covariance matrix by assuming treatment effects on some of the outcomes are conditionally independent.
While the two models are developed for the summary data on a study level, the individual-level association is taken
into account by the use of the Prentice’s criteria (obtained from individual patient data) to inform the within study
correlations in the models. The modelling techniques are investigated using an example in relapsing remitting
multiple sclerosis where the disability worsening is the final outcome, while relapse rate and MRI lesions are
potential surrogates to the disability progression.
History
Citation
Statistics in Medicine, 2016, 35 (7), pp. 1063-1089
Author affiliation
/Organisation/COLLEGE OF MEDICINE, BIOLOGICAL SCIENCES AND PSYCHOLOGY/School of Medicine/Department of Health Sciences
Correction to: Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process (Statistics in Medicine, (2016), 35, 7, (1063-1089), 10.1002/sim.6776) Correction: https://doi.org/10.1002/sim.9597 I would like to report an erratum to the paper titled 'Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process' by Bujkiewicz, Thompson, Riley and Abrams, Statistics in Medicine